Reviewerly/exHarmony huggingface dataset:
Cloud-based Salesman-Bot for Ontology-based Negotiation

We have proposed a cloud-based ChatBot (Salesman-Bot) approach to handling multiple negotiation scenarios in a supermarket environment. The web application is a simple interface that can be implemented on a single standalone device or interacted with through a mobile phone. The Salesman-Bot responds both via text and speech. By introducing a Salesman-Bot, efficient negotiation, with quick preferences and suggestions can be provided. A new architecture proposed to operate the Salesman-Bot together with Google APIs and libraries such as Natural Language AI, Vision AI, Speech to Text API, Text to Speech API and Machine Learning using TensorFlow. The application also uses the Google Cloud Platform with related services such as Google App Engine. The goal is to make ChatBots more efficient in negotiating in different business scenarios. This paper presents the work carried out with ontology and machine learning in a cloud-based environment to handle multiple negotiation scenarios based on a negotiation hierarchy. It also proposes the opportunities and drawbacks of such a system.
Reliability Analysis and Risk Warning Strategy of Power Communication Network Based on SG-EA Architecture

In order to eliminate hidden problems and prevent failures in power communication network in advance, a reliability analysis and risk warning strategy of power communication network based on SG-EA architecture is proposed, which includes the processes of establishing a common data model for resources, establishing protection relationship model, and risk warning of power communication network. A hierarchical quantitative standard algorithm of communication network risk warning indicators is proposed to clearly and quantitatively classify the levels of communication network risk warning. The indicator warning and indicator-trend warning fusion algorithm is designed to realize the comprehensive analysis of power communication network, so as to obtain the risk warning results of graded disposition. This strategy can use the performance collection and analysis of network and equipment to control the trend of resource changes, so as to arrange proactive and targeted risk pre-control or maintenance work before the occurrence of failure.
The Day a System Becomes a Conversation Partner—Exploring New Horizons in Social Dialogue Systems with Large-scale Deep Learning

People live their lives by casually talking with others on a daily basis.Such "social" dialogue contributes to building trust among people and satisfying their desire to talk with others.There has been a growing interest in social dialogue systems to satisfy the human desire for chatting with others, and we have been working on a wide range of research projects to develop such systems.With the rapid progress in deep learning, high-performance social dialogue systems using deep learning have been proposed.In this article, we introduce NTT's social dialogue system using the latest deep-learning models as well as the current achievements obtained and challenges with this system.
Developing AI that Pays Attention to Who You Want to Listen to: Deep-learning-based Selective Hearing with SpeakerBeam

In a noisy environment such as a cocktail party, humans can focus on listening to a desired speaker, an ability known as selective hearing.In this article, we discuss approaches to achieve computational selective hearing.We first introduce SpeakerBeam, which is a neural-network-based method for extracting speech of a desired target speaker in a mixture of speakers, by exploiting a few seconds of pre-recorded audio data of the target speaker.We then present our recent research, which includes (1) the extension to multi-modal processing, in which we exploit video of the lip movements of the target speaker in addition to the audio pre-recording, (2) integration with automatic speech recognition, and (3) generalization to the extraction of arbitrary sounds.
FORMATION OF INCLUSIVE COMPETENCE OF EDUCATORS DURING FACE-TO-FACE CLASSES AT ADVANCED TRAINING COURSES

The article examines the peculiarities of the formation of inclusive competence for teachers of all specialties and educators of preschool education institutions, describes the disadvantages and advantages of face-to-face training on the order of an educa
Prediction Model of hospitalization time of COVID-19 patients based on Gradient Boosted Regression Trees

When an outbreak of COVID-19 occurs, it will cause a shortage of medical resources and the surge of demand for hospital beds. Predicting the length of stay (LOS) of COVID-19 patients is helpful to the overall coordination of hospital management and improves the utilization rate of medical resources. The purpose of this paper is to predict LOS for patients with COVID-19, so as to provide hospital management with auxiliary decision-making of medical resource scheduling. We collected the data of 166 COVID-19 patients in a hospital in Xinjiang from July 19, 2020, to August 26, 2020, and carried out a retrospective study. The results showed that the median LOS was 17.0 days, and the average of LOS was 18.06 days. Demographic data and clinical indicators were included as predictive variables to construct a model for predicting the LOS using gradient boosted regression trees (GBRT). The MSE, MAE and MAPE of the model are 23.84, 4.12 and 0.76 respectively. The importance of all the variables involved in the prediction of the model was analyzed, and the clinical indexes creatine kinase-MB (CK-MB), C-reactive protein (CRP), creatine kinase (CK), white blood cell count (WBC) and the age of patients had a higher contribution to the LOS. We found our GBRT model can accurately predict the LOS of COVID-19 patients, which will provide good assistant decision-making for medical management.
Dmitry Vasilievich Rundqvist - an employee of VSEGEI (1954-1984)

Dmitry Vasilievich Rundqvist (1930-2022) is an outstanding Soviet and Russian geologist, mineralogist and metallogenist, Doctor of Geological and Mineralogical Sciences, Professor, President of the Russian Mineralogical Society (1987-2015), Academician of the Russian Academy of Sciences, full member of the Academy of Mining Sciences. He made an important contribution to theoretical geology and metallogeny: he investigated the processes of mineral and ore formation, and analyzed the most general trends in the evolution of mineral formation in geological history. He is credited with developing the structural-material principles for separating, classifying and establishing the ore content of geological formations, and creating a series of specialized metallogenic maps that reflect the main regularities in the distribution of mineral deposits and a quantitative assessment of the predicted resources of promising regions of the USSR. The formation of D.V. Rundqvist as a prominent metallogenist was held at the All-Union Scientific Research Geological Institute (VSEGEI), where he worked for 30 years, rose from junior researcher to deputy director for science. The period of work of D.V. Rundqvist in VSEGEI is dedicated to this essay.
REMOTE ACCESS TO MOBILE ROBOT

The relevance Due to constantly changing market conditions, high decision-making speed, multitasking and the need to reduce risks, more and more modern approaches are required in the organizational activities of enterprises. Currently, companies have begun to actively migrate to the digital space, creating and developing their information systems with remote access support. According to the survey results of the TAdviser portal, 35 % of companies have transferred more than 50 % of their employees to a remote or hybrid work format. Another 18 % of respondents shared that in their companies 25 % to 50 % of employees work remotely. However, the control of robotic systems requires periodic monitoring. To manage such platforms, enterprises need to create interfaces and provide them with remote access. Therefore, using a chatbot as an interface for remote access to mobile robots can provide an alternative solution to this problem. The use of chatbots provides user service around the clock, which allows you to instantly receive the necessary information, collect data and automate the process of interaction between the user and the robot. Aim of research The main aim of the research is to explore the possibility of using a chatbot to provide remote access to inaccessible or hard-to-reach places for humans. Design and create an information system for research. Research methods To achieve the study aim, it was decided to conduct a physical simulation. A certain technical composition for the mobile platform was chosen and a chat bot was written to interact with the robot. Results A chatbot has been developed and manufactured with which you can control the movement of the robot and connect to its camera. It was decided to use Python as the main programming language. The platform for the implementation of the information product is Telegram, which is multiplatform, its versions are available for iOS, Android, Windows, Linux. In addition, it is possible to use the messenger through a web browser.
Implementing The Multimodal Communication Modes On Telegram Bot Elia

Information related to lectures in a study program must be conveyed clearly and carried out regularly.Even though the information has been delivered routinely and centrally, students sometimes miss the announcement.This condition causes the need for a more effective method of accommodating FAQs (frequently asked questions) so that students can find information related to lectures, proposal exams, thesis exams, and other information related to study programs.This study aims to implement four essential components in the multimodal communication model in conveying information in the English Literature Study Program, Faculty of Letters, Universitas Warmadewa in providing fast and accurate information.This research is field research located in the English Literature Study Program, Faculty of Letters, University of Warmadewa.The data sources are documents and policies in the English Literature Study Program.Data were collected from academic guidelines, proposal & thesis guidebooks, academic calendars, curriculum, and other documents that support the educational process at the English Literature Study Program.FAQs were collected through interviews with the Head of the English Literature Study Program.This study shows the use of textual modes organized in categories
How EFL teacher Modelling Politeness: Pragmatic Analysis of Classroom Interaction

Purpose- This study aims to find the types of politeness strategies used by English teachers during the learning process.&#x0D; Design/methodology/approach- This study uses a qualitative research method with ethnographic communication design to find politeness strategies in speech used by English teachers at SMA Negeri 1 Prambon. Research data were taken through observation and interviews. Researchers used a coding scheme to analyze the data that has been obtained.&#x0D; Findings/results – It was found 134 teacher utterances, classified according to politeness strategies that were applied during the English learning process. Of the 134 teacher utterances, there are 35 utterances categorized as positive politeness strategies, 8 utterances as negative politeness strategies, 69 as bald on-record politeness strategies, and 22 utterances as off-record politeness strategies. In other words, the bald on-record strategy is the dominant politeness strategy used by English teachers during the learning process. Thus, the politeness strategies used by teachers are influenced by certain conditions and situations in the classroom.&#x0D; Originality/value - Politeness strategy is a very crucial thing which needs to be considered in its use based on the appropriate conditions and situations, especially by the teacher as an example or role model for his students is not the case in the delivery of subject matter but also attitude or speech.&#x0D; Paper type – Research paper &#x0D; Keywords: Teacher talk, pragmatic, politeness strategies
Qur’an tilawatil examination system

A group Decision Support System (GDSS) is used when a decision system has many stakeholders providing recommendations in a system. One of them is the Tilawatil of the Qur'an for students in the religious field test. The assessment consists of several raters. The purpose of this study is to apply the SMART (Simple Multi-Attribute Rating Technique) and Borda methods in calculating the results of the Tilawatil Qur'an test based on a decision support system. The SMART method is used in assessing the results of the Tilawatil Qur'an test and the Borda method is used in optimizing the overall results of the assessors on the SMART method. The results of the study were based on the SMART value accuracy test manually with the system yielding 95%. After that, the results of the optimization test of the Borda method were calculated by calculating the average value of the SMART method with optimal ranking results.
La Dichiarazione europea per lo studio del latino e del greco antico: filologia e autenticità dei beni culturali

On November 26, 2021, the Ministers of Education of four countries - Italy, France, Greece and Cyprus - signed a memorandum of understanding for the defense and enhancement of classical languages, publishing a joint declaration in which they undertake "to strengthen cooperation in the study of Latin and Ancient Greek, encouraging and developing bilateral and multilateral partnerships', with the aim of promoting knowledge of these languages. The document explicitly recognizes Latin and Greek as European intangible heritage both for their historicity and for the economic value connected to them. Classical languages, vehicle of the intangible heritage and essential defense tool, are explicitly linked for the first time with scientific progress, eliminating a dangerous dichotomy, recently invaded, between theory and practice, between philological studies and scientific skills, and reiterating that it is not possible to know the past and intervene in the future without the necessary presence of the linguistic codes that have generated the culture of humanity. The contribution aims to elaborate and order the value of ancient media as a scientific tool for the generation and dissemination of the cultural characteristics of modern man.
Prediction of flood events in the city of Bandar Lampung using the artificial neural network

The city of Bandar Lampung is currently experiencing seasonal flooding which occurs almost every year, resulting in significant losses. Floods recorded by BNPB in the last 10 years there were 16 incidents of flooding in the Bandar Lampung area. More than 14,000 people suffered, more than 500 people had to be evacuated, more than 900 houses were damaged, and 4 public facilities were damaged. To study the pattern of flood events in the past, the Artificial Neural Network Backpropagation learning method will be used which will utilize its non-linear variable learning abilities. The configuration settings for the Artificial Neural Network were carried out experimentally without any basis for assigning values, especially for the parameters of the number of hidden layers, number of neurons, and epochs used in training and variable testing. The results obtained from this study are the results of training and testing of datasets that have been carried out by ANN backpropagation are able to properly study patterns of flood events and also non-flood events in the dataset, this is evidenced by the results of high model configuration accuracy and also the results of predictive tables that able to describe actual conditions, setting the configuration model experimentally is able to produce an accuracy value of 90-100%, an average training correlation value of 0.96 and an average test correlation value of 0.89, and an average error value of 0.0089 out of 20 model configuration, and the flood prediction table are made based on the 1 best configuration with a training and testing accuracy rate of 100% with an error value of 0.00134, namely configuration model 20, the prediction table uses an average air temperature of 27˚C with 80% humidity. The prediction table is able to produce excellent flood potential results which are able to represent flood events as well as non-flood events based on the results of the dataset learning.
Application of the k-means clustering method and simple linear regression to new student admissions as a promotion method

At private label universities in Indonesia, new students are still the main thing in terms of achieving university operational income. This study intends to group the data of ITTelkom Surabaya students by utilizing the data mining process using the k-means clustering method, then the results of the clustering are forecasted using simple linear regression to be able to predict the achievement of new students as the effect variable and year as the causative variable. The results of this study consist of 5 variables, namely student province, student study program, income of student parents, student parent work and student ethnicity, each of which consists of 4 clusters, then each cluster is predicted for achievement 3 the coming year 2022,2023,2024. It can be concluded that the highest combination of student/parent student profiles was obtained from East Java province, information systems study program, parents' income of 5-10 million per month, the occupation of other parents and the ethnicity of students from Java. The highest forecasting results are found in the income variable of students' parents in cluster 3 with predictions of 1292 students in 2024. It is hoped that with clustering and forecasting based on this research, ITTelkom Surabaya can make the right decision as a basis for decision making to determine strategy in promoting the campus.
Reformulating the Basics of Conventional Newtonian Physics, Quantum Physics and the Einstein Theories of Relativities Based on the newly discovered Topological Theory of Quantum Gravity (TTQG)

The Newtonian physics, quantum physics and the theories of relativity suffer from a major Incompleteness on the ground of being unable to offer the topologies and the dimensionalities of the numerous physical variables. Out of the three very familiar dimensions of physical variables in conventional physics length (L), mass (M) and time (T), the two variables, namely mass and time are fully arbitrary and abstract. In Newtonian physics L, M and T are fully independent variables since no mathematical equation linking the said three variables have been proposed. It is an established fact and a matter of everyday experience that L, M and T are very much linked to each other and otherwise which, the universe could have taken either the infinite number of shapes of desire arising out of endless permutations and combinations of L, M and T or could have merged to fully length (LM°T°) or fully mass (L°MT°) or fully time (L°M° T). Max Planck tied up the five numbers of basic physical variables, length, time, mass, electric charge and temperature to the same source by linking all of them to the Newton’s Gravitational constant (G) and Planck constant (h). However, this attempt was also incomplete since the topologies of G and h, could not be put forward. Later on, the quantum physics even, could not erase the stamp of ‘abstractness’ as put on the physical variables like mass, time, temperature, gravitation, photon waves and many others. Neither the Newtonian physics nor the quantum physics can depict the dimensionalities of entropy, force, energy, acceleration, black hole, plasma state, etc. and as well cannot also tell us how a ‘photon’ looks alike or what the ‘gravitons’ are in reality. The recently discovered topological theory of quantum gravity (TTQG) revealed the following: 1. The phenomenon of gravitation is being linked to the intermolecular attractive forces. 2. Have defined all the above said physical variables as ‘gravitons’ in regard to entropy. 3. Presented the topologies and dimensionalities of the physical variables. 4. Introduced the inverse dimensionality concept in physics. 5. Proposed the mathematical equation relating L, M and T 6. Reformulated the basics of Newtonian physics, quantum physics and the special and general theories of relativity. 7. All the cosmic phenomena of the universe have been represented by a singularity graviton originated universal graviton cycle.
The Essence of Human Hearing

The experimental data of the sound, investigates by Fletcher and Munson, were analyzed to interpret the feeling-effect of Pythagoras, being the fundamental motivation of singing and music in general. It has been pointed out that this feeling-effect is beyond any reality. Moreover, it is shown that the minimum wave related energy of sound, considered in relation to the energy of a single electron, enables to determine the relation between the natural, i.e. the wave related time, and the artificial, i.e. with the human life connected time. This observation suggests the idea that the artificial time appears to be causally related to the time of the breaking of the human voice, the mutation. This spectacular idea has been confirmed by experimental data, showing that both the difference between the energy of the single electron and the minimum sound energy, as well as the difference between the artificial, i.e. the human related time, and the natural time, yield the same order of magnitude of 1012.
IMPROVING STUDENT LEARNING OUTCOMES THROUGH THE USE OF DIGITAL LEARNING MEDIA

The success of a learning including by utilizing learning media. But in fact the use of learning media is still not used optimally. digital learning media is one of the media to improve student learning outcomes. This study aims to determine the use of digital learning media to improve student learning outcomes. The design of this study was a true experimental study with a Pretest-Posttest Group Design. Learning outcomes data were obtained through pretest and posttest activities. The sample was 80 students who were taken randomly by adjusting the conditions and research objectives. There is a significant difference in the posttest results of the experimental class and the control class, this is evidenced by the value of Fo. For the value is 5.225 and Sig is 0.025 &lt; 0.05. This means that there is a difference in the interaction effect of using digital learning media to improve student learning outcomes
The (Present) Age of Quantum Computing

Quantum computing is an intense and challenging research area, that promises to change the world we live in. But what is its current status, both in terms of understanding and applications? We discuss some points related to this question in this article.
EFEKTIVITAS GERAKAN LITERASI DIGITAL DI SEKOLAH JENJANG PENDIDIKAN DASAR DI KOTA PONTIANAK

The purpose of this study was to obtain information on the effectiveness of the digital literacy movement and what factors influence the effectiveness of the digital literacy movement in Sekolah Dasar Negeri dan Sekolah Menengah Pertama Negeri Kota Pontianak. The research approach used is quantitative research and descriptive study. The data for this study were sourced from schools, especially from principals and teachers, with details as many as 141 Sekolah Dasar Negeri and 28 Sekolah Menengah Pertama Negeri. The data collection technique is direct communication by conducting interviews with principals, teachers and students. Analysis of research data using Content Input Process and Product (CIPP) analysis, then the data is analyzed using SPSS statistics program. The digital literacy movement in Pontianak State Elementary Schools and Junior High Schools in general is still not effective. Judging from the class base, school culture base, and community base. There are several factors that influence the effectiveness of the digital literacy movement in Sekolah Dasar Negeri dan Sekolah Menengah Pertama Negeri Kota Pontianak.