Reviewerly/exHarmony huggingface dataset:
A Multi-source Heterogeneous Data Storage and Retrieval System for Intelligent Manufacturing

The manufacturing industry produces massive multi-source heterogeneous data such as text, images, audio, and video in the process of design, production, sales, and service. The major problem facing manufacturing companies is how to efficiently manage and use these data resources to create value for manufacturing reproduction. Traditional data storage and retrieval systems classify heterogeneous data according to different forms or modalities and process them separately, resulting in a lack of correlation between cross-modal data (text, image, audio, and video data cannot be checked each other). It cannot support the problem of manufacturing business processes. In this article, we designed and implemented an efficient and fast cross-modal retrieval system for multi-modal industrial data such as text and pictures to realize efficient management and retrieval of multi-source heterogeneous data. Specifically, the system calculates the multi-modal content of manufacturing design, product, service, and other data as a set of unified semantic expressions and stores it in the index structure. When the user makes a query, the index system will return all the modal data related to the retrieved content. This article conducted experiments on the Flick30k data set. The experimental results show that: (1) This system can support millions of data storage and retrieval. (2) With millions of data, the system retrieval rate is in milliseconds. (3) The retrieval accuracy is higher than traditional vector retrieval methods.
Socio-methodological aspects of the development of the flagship university

Introduction. The article examines the specificity of the flagship university – a new component in the regional development of structures related to higher education, economics and management. Purpose setting. The objective of the study is to analyze the list of scientific and pedagogical competencies, which (due to its novelty) it has not yet been fully formed by scientists in the form of a clear system of knowledge. The identification of this so-called unstructured list of scientific and pedagogical competencies is necessary to improve the system style in the implementation of educational and pedagogical activities of the specialists of the flagship university. Methodology of the study. The methodology of the analysis of the material included in the article is based on the principle of interaction of intersectoral and interdisciplinary types of scientific and technological activities. Results . The article reveals the content of the innovation policy of state, at the regional level of which the solution of complex socio-economic problems is inextricably linked with the activities of the flagship university. The flagship university is new educational component in the system of interaction between government, science and entrepreneurship. The comparative analysis of research approaches has revealed an unstructured list of competencies of a scientific and pedagogical employee of the university necessary for the implementation of educational activities. Since educational activities are aimed at the formation of certain professional competencies and values among students, the priority personal qualities and socio-professional competencies of university teachers are highly specialized skills and general erudition, methodological thinking, continuous professional development, motivation for pedagogical work, communicative abilities. Pedagogical activity at universities is associated with the participation of a teacher in research work. The novelty of our research consists in structuring the list of personal qualities and socio-professional competencies of a modern teacher and student that are in demand in relevant fields of activity/ Conclusion. Based on the results achieved in the process of analyzing publication materials, the paper summarizes the innovative ability of the flagship university to implement specifi management projects, improve personal competencies, make informed decisions when selecting specialists and personnel changes. The results of the study can be used by university teachers in the framework of building subjective perspectives of professional and personal development.
Nonnegative matrix factorization with combined kernels for small data representation

Kernel nonnegative matrix factorization (KNMF) has emerged as a promising nonlinear data representation method, especially for applications with small sample sizes. Existing methods are usually based on a single kernel function, representing samples by the global or local features learned by the matrix factorization algorithm. In this paper, a combined kernel method is proposed and applied to data representation for small-sample face recognition in particular. Based on the combined kernel, which is a linear combination of the fractional power inner-product kernel and a newly defined Gaussian-type kernel, the new KNMF method is able to extract both global and local nonlinear features from the inputs. An efficient gradient decent algorithm is derived to solve the combined kernel nonnegative matrix factorization (CKNMF) problem, and a rigorous convergence proof is presented. The proposed method is experimentally evaluated on small image datasets, and the results demonstrate its superior performance than the state-of-the-art KNMF methods.
A dataset of Tibetan text summarization

Automatic text summarization is a key task in natural language processing. High-quality datasets can effectively promote the research progress of summarization. Recent research is closer to generate abstractive summarizations by using the deep learning methods. However, there is a lack of high-quality and large-scale summarization datasets available to the public. Besides, it is difficult to construct this kind of dataset manually. The Tibetan text summarization task is still in its infancy due to the lack of public datasets. In order to promote the development of Tibetan informatization. we artificially constructed a small dataset of Tibetan text summarization in this paper, which is composed of 1,000 real Tibetan news articles, each with a short summary. In addition, we have also constructed more than 3,500 article keywords for each news article as a supplement to text summarization tasks.
IMUT-MC: a speech corpus for Mongolian speech recognition

There is a lack of large-scale speech corpora of Mongolian (a minority language) accessible to researchers for experimental reference, because its users are scattered and it is difficult to collect and label the speech sounds, which hinders the further development of Mongolian speech recognition.Our research group has constructed a speech corpus IMUT-MC for Mongolian speech recognition tasks, which contains about 212 hours of reading speech recorded by 417 speakers, and we are committed to advancing Mongolian speech recognition research. The research group used IMUT-MC to conduct baseline speech recognition experiments on traditional speech recognition models and end-to-end speech recognition models respectively. The speech recognition models based on GMM-HMM, DNN-HMM and Transformer have word error rates on IMUT-MC, respectively. 69.90%, 67.45% and 26.10%, which proves that IMUT-MC is a reliable corpus for Mongolian speech recognition.
Revised SAMPL Guidelines for Reporting of Statistical Methods in Biomedical Journals

Many of these problems can be addressed by following standard guidelines for statistical reporting. Reporting guidelines such as CONSORT, STROBE and STARD have improved the quality of research in addition to helping in complete reporting9. In realization of this potential, Lang and Altman10 developed a set of guidelines for reporting of basic statistical methods and called it "Statistical Analyses and Methods in the Published Literature" (SAMPL) guidelines. However, these guidelines were not in the standard format, had some duplication, and some important points escaped attention. Indrayan11 organized them in the standard item wise format on the pattern of CONSORT, STROBE and STARD guidelines, removed the duplication, and included the items earlier escaped. Such improved guidelines are presented in . These are described in a manner that a statistically literate medical researcher can adopt without much help of a statistician. First 13 items in this list will be required by almost...
APPLIED ISLAMIC BIOETHICS: TRANSNATIONAL EXPERIENCE OF ETHICAL AND LEGAL PROBLEMS

The article discusses the trend of secularization of bioethics issues in Islam, the relevance of scientific research in the West, in which 10 priority among the many bioethical issues in Islam have been identified. Experience of Islamic international organizations in addressing ethical and legal problems of bioethics has a transnational nature, which can provide an ethical consensus of Muslim discourse in situations of complex bioethical pluralism in the Muslim world.
Covid-19 Android chatbot using RASA

The COVID-19 pandemic, a flood of information and news from various sources has raised numerous questions in people's thoughts concerning the disease. COVID-19 is a coronavirus, which encompasses the Severe Acute Respiratory Syndrome (SARS) virus and Middle East Respiratory Symptoms (MERS) virus. Coronavirus is a virus family that comprises virus types that cause the flu and the common cold.Chatbots and voice assistants are becoming increasingly popular ways for people to connect with systems. The days of interacting with services simply through a keyboard are long gone. Artificial Intelligence and Machine Learning developments have contributed to the development of these new types of user interaction. We'll focus on the development of chatbots as a channel for information distribution via an Android application in particular. With over 2.5 billion active users globally and over 3 million devices utilizing this Android application, it is certain to reach a large number of people.A chatbot is proposed in this study to eliminate information pollution, including false information regarding COVID19, and to provide the right responses to people's concerns. In the realm of natural language processing, a chatbot is a popular discussion system (Natural Language Processing). Chatbots are software that allows computers and people to converse. The chatbot is created on the Android platform and uses the RASA [13] open-source framework to answer inquiries regarding COVID-19. It also offers a Rapid API [14] that keeps information on COVID-19 up to date. It delivers correct information by updating the material on a regular basis.
The Efficacy of Online Higher Education in Latin America: A Systematic Literature Review

The objective of this systematic review and meta-analysis is to summarize the Spanish and English language literature that compares the academic performance of Latin American university students in online and face-to-face courses. Research questions focus on trends, mean differences, and the significance of the findings. It includes peer-reviewed articles published between 2005-2020, found in EBSCO/ SciELO/ HAPI/ WOS/ Scopus databases, that offer an experimental or quasi-experimental research design to analyze efficacy; articles with case studies outside Spanish-speaking Latin America, focusing on K-12/post-graduate education, and/or solely including satisfaction/ qualitative measures were excluded. The final 35 articles analyze courses mostly based on a hybrid pedagogy used for a treatment section. After removal of value-added observations, results on 30 outcomes were synthesized in descriptive tables, forest and funnel plots. In most cases, online components do no harm to students of a given course; outcomes increase significantly in 57% of the cases, using a sample of over 10,000 student observations. Intermediate effect sizes from the online innovations are over 0.60 (intervals [−0.13-1.470]) and largest when student achievement is the outcome. Publication limitations include limited student background information, unclear sorting across sections, and small sample sizes which suggest caution in the interpretation of results.
Type-$(2,k)$ Overlap Indices

Automatic image detection is one of the most important areas in computing due to its potential application in numerous real-world scenarios. One important tool to deal with that is called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">overlap indices</i> . They were introduced as a procedure to provide the maximum lack of knowledge when comparing two fuzzy objects. They have been successfully applied in the following fields: image processing, fuzzy rule-based systems, decision making, and computational brain interfaces. This notion of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">overlap indices</i> is also necessary for applications in which type-2 fuzzy sets are required. In this article, we introduce the notion of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">type-<inline-formula><tex-math notation="LaTeX">$(2,k)$</tex-math></inline-formula> overlap index</i> ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$k \in \lbrace 0,1,2\rbrace$</tex-math></inline-formula> ) in the setting of type-2 fuzzy sets. We describe both the reasons that have led to this notion and the relationships that naturally arise among the algebraic underlying structures. Finally, we illustrate how type- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$(2,k)$</tex-math></inline-formula> overlap indices can be employed in the setting of fuzzy rule-based systems when the involved objects are type-2 fuzzy sets.
Comparison of Blockly vs Arduino IDE for programming education using M5Stack Core2 ESP32 IoT Development Kit

STEAM education promotes programming at all levels of training, being block programming a compatible alternative, including the development of applications with hardware. This paper presents a comparison between Blockly and Arduino IDE in programming the M5Core2 Core2 ESP32 IoT Development Kit for educational purposes. For the study, a program is designed that allows students to read, view a send the data of the inertial sensor integrated in the device. The programming in Blockly is carried out in the UIFLOW application developed for the M5stack cards and the program in Arduino IDE is carried out by installing the necessary libraries for compatibility with this device. The program is evaluated by students of computer science engineering using both programming languages, the participants must answer an acceptance test at the end of the sessions to measure the level of satisfaction with learning. The results show the implementation times of the programs and the scores obtained, determining faster times in the case of Blockly programming and a better acceptance rate that demonstrates the advantages of using this language in programming education.
Recognizing Human Activities of Daily Living Using Mobile Sensors for Health monitoring

In today’s world, technology is helping human life everywhere. Human activity recognition (HAR) is one of the pioneer research areas of computer vision which is evolving rapidly to help human daily needs. During this pandemic situation, where people cannot travel frequently, remote monitoring of a person’s activity is very important and the research on HAR plays a big role in it. HAR helps a person to remotely monitor or recognize another person’s activity through mobile apps or by using sensor-based Internet of Things (IoT) devices. This shows future possibilities of its application in linking different types of healthcare professionals and medical devices to deliver standard medical services in an outlying location. It can be applied in various domains such as mobile apps and healthcare systems. In our study, it was a very challenging area of research to identify what the person was doing at a particular time frame. We concentrated on the accurate identification of different daily-life human activities based on the accelerometer and gyroscope values with a pre-trained transfer learning model. The proposed model has been tested on MobiAct v2 dataset and the experimental results are found to be impressive with respect to the state-of-the-art models.
Measuring failed disruption propagation in genetic programming

Information theory explains the robustness of deep GP trees, with on average up to 83.3% of crossover run time disruptions failing to propagate to the root node, and so having no impact on fitness, leading to phenotypic convergence. Monte Carlo simulations of perturbations covering the whole tree demonstrate a model based on random synchronisation of the evaluation of the parent and child which cause parent and offspring evaluations to be identical. This predicts the effectiveness of fitness measurement grows slowly as O(log(n)) with number n of test cases. This geometric distribution model is tested on genetic programming symbolic regression.
Teaching Practical Research Data Management Skills through Online Training and Data Management Plan Creation

Introduction: Research Data Management is growing in importance as a field as the amount of data which researchers must manage increases. It is important to ensure that postgraduate researchers are trained through engaging courses which practically prepare them to fulfil the data management requirements of funders and Universities, and to carry out their research in a transparent and effective manner. Description of program: We present a case study of the development and delivery of a new Research Data Management (RDM) online course for postgraduates and early career researchers. The course implements pedagogical theory and a reverse design paradigm in the development of library training provision enabling the creation of a course vastly more relevant to academic research practice than our previous offering. The course uses a simplified Data Management Plan to introduce students to Research Data Management Concepts, and by asking them to apply this knowledge, lifts the course from one which simply asks students to remember knowledge to one which shows them how to apply this knowledge in a way that is applicable to their own research. The course has been evaluated for effectiveness and student engagement at 3 months. Next steps: Although some analysis of the effectiveness of the new course has been undertaken, the course will continue to be evaluated. Although the course was developed for PGRs it has been popular with ECRs and Professional support staff and we will investigate how we can further meet the needs of these groups. The platform used will allow for the topics most often accessed to be identified and the course, and the University’s training provision will be adjusted based on this evidence. We hope that other institutions will be able to learn from our experience and implement similar courses.
PEMBUATAN APLIKASI E-LEARNING PADA SMK SWASTA PARIWISATA IMELDA MEDAN

SMK Swasta Priwisata Imelda Medan is one of the private vocational schools in Medan. Learning system at SMK Swasta Priwisata Imelda Medan still use manual system which means the teaching and learning process is still bound by the time the subjects are available and must meet face-to-face with subject teachers. Subject material in the SMK Swasta Pariwisata Imelda Medan is quite difficult so that teachers and students need a long time in teaching and learning. to support an effective learning system at SMK Swasta Pariwisata Imelda Medan needs to be made an e-learning based learning system that is e-learning. the author uses the php language, mysql, dreamweaver and Xampp Control Panel Version 2.5.8, to provide solutions in the process of learning and teaching at SMK Swasta Pariwisata Imelda Medan in order to facilitate students and teachers in teaching and learning without the time limit provided by the school
Human or nonhuman agent?

Digitalisation of services offers several possibilities to enhance the tourism experience as technology is increasingly mediating experiences. Along with the development of the service concept, digital transformation has been extended to services in which the customer may interact with a human agent or a technology-provided nonhuman agent. With digital services increasingly becoming mediating experiences, there is a constant need to balance them with empathetic customer insights to perceive a holistic understanding of each customer’s needs. Empathy is a critical part of ethics and morality because it requires one to experience otherness when acknowledging the perspectives and well-being of others in situations that are not necessarily beneficial to oneself. Technology-provided nonhuman agent services have a significant role in digital transformation where traditional services like data and activities are reformed and new services are developed.
Bayesian optimization

tutorial Share on Bayesian optimization: tutorial Authors: Ivo Couckuyt View Profile , Sebastian Rojas Gonzalez View Profile , Juergen Branke View Profile Authors Info & Claims GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference CompanionJuly 2022 Pages 843–863https://doi.org/10.1145/3520304.3533654Published:19 July 2022Publication History 0citation93DownloadsMetricsTotal Citations0Total Downloads93Last 12 Months93Last 6 weeks25 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
EXPERIENCES WITH THE USE OF VIRTUAL REALITY ENVIRONMENTS IN EDUCATION – IDENTIFYING DIFFICULTIES AND POSSIBLE SOLUTIONS DURING THESIS WORK

EXPERIENCES WITH THE USE OF VIRTUAL REALITY ENVIRONMENTS IN EDUCATION – IDENTIFYING DIFFICULTIES AND POSSIBLE SOLUTIONS DURING THESIS WORK
Development of a low-cost wearable device for Covid-19 self-quarantine monitoring system

The objective of this study is to develop a Bluetooth-based low-cost wearable device for a self-quarantine monitoring system. The designed wearable device focuses on data transmission via Bluetooth, integration of tracking, tracing, and fencing into a single system, and low energy usage from its battery. We design a wearable device using smartphone equipped with GPS, a communication module, Bluetooth low energy (BLE) and a high-capacity battery as a solution for low-cost device with excellent efficiency. We divide the designed system into two parts, the client and the server parts. The client parts are wearable device attached to the individual being monitored and the mobile phone as GPS and telecommunications module. Whereas the server parts are user interface, digital map, notification system, and backend database. Then, the whole system was tested in laboratory and field scale. We tested functions of integrated device such as wearable device, mobile applications, and server for laboratory scale test. Then, performing field test with geofencing, communication module, battery, web interface, and resource computing usage. The field test was conducted on a small scale with a limited number of trial patients. We found that the designed wearable device was successfully implemented for both self-quarantine and centralized quarantine requirements. The majority of the components used met the specifications and functioned properly as well. A BLE-enabled wearable device can be used for tracking self-quarantine patients. The laboratory and field scale tests demonstrate that the designed wearable device functions properly and meets the requirements. We anticipate that this low-cost wearable device is effective in limiting Covid-19 virus spread and preventing the formation of a new Covid-19 virus-infected cluster.