Reviewerly/exHarmony huggingface dataset:
MOVIE RECOMMENDATION USING KNOWLEDGE GRAPH

The Knowledge graphs (KGs) catches structured data and relationships among a bunch of entities and items. Generally, constitute an attractive origin of information that can advance the recommender systems. But, present methodologies of this area depend on manual element thus don’t permit for start to end training. This article proposes, Knowledge Graph along with Label Smoothness (KG-LS) to offer better suggestions for the recommender Systems. Our methodology processes user-specific entities by prior application of a function capability that recognizes key KG-relationships for a specific user. In this manner, we change the KG in a specific-user weighted graph followed by application of a graph neural network to process customized entity embedding. To give better preliminary predisposition, label smoothness comes into picture, which places items in the KG which probably going to have identical user significant names/scores. Use of, label smoothness gives regularization above the edge weights thus; we demonstrate that it is comparable to a label propagation plan on the graph. Additionally building-up a productive usage that symbolizes solid adaptability concerning the size of knowledge graph. Experimentation on 4 datasets shows that our strategy beats best in class baselines. This process likewise accomplishes solid execution in cold start situations where user-entity communications remain meager.
STEM CONCEPT IN THE WORK OF THE MATERIALS RESEARCH GROUPS OF THE SMALL ACADEMY OF SCIENCES

The article is devoted to STEM-direction, which gained world recognition as one of the main modern reformative tendencies in the natural and technical education field. The experience of cooperation between the Junior Academy of Sciences of Ukraine and the Lutsk National Technical University in the field of extracurricular education is presented in the article. The materials science research program provides an integration of the content and methodology of the natural sciences, technology, engineering and mathematics, and logical thinking into collaboration and research. The purpose of the curriculum is to develop key and subject competencies of individual by means of scientific research in materials science. Doubtless advantage of the group is a possibility of doing numerous experiments related to the study of the structure and properties of substances and materials. Classes in the materials research group are aimed at developing the ability to analyze the tasks set, apply the acquired knowledge in practice, give the opportunity to formulate the experience, its implementation and processing of the obtained results. Presentations of scientific achievements at competitions develop students’ creative abilities and practical skills. It is established that the STEM approach to after-school learning promotes the effective development of scientific and technical creativity of students. Cooperation of Technical University and Small Academy of Sciences promotes the development of key and subject pupils competencies, the deepening of their knowledge and the development of new skills, professional self-determination. A significant argument for the efficiency is the numerous victories of pupils at competitions of scientific and technical creativity of students, such as “Intel-Eco”, “Intel-Techno”, “Future of Ukraine”, “Crystals”, competition-defense of scientific works of the Academy of Sciences.
군 장비의 창정비와 성능개량 결정요소 실증분석

For the purpose of achieving the required performance level of the military equipments, not only proper maintenance activities, but also timely product improvement programs are necessary within the life time of the equipments.The Ministry of National Defense currently reports that combined execution policy of depot maintenance activities and product improvement programs with some military equipments turns out remarkable decrease of budget amount at the operating stage. However, while keeping each activities under the independent rule, organization and budget program, such combined execution policy barely can carry out further and deeper. Using the FGI(Focus Group Interview) and AHP(Analytic Hierarchy Process) consecutively, we could conclude the key common decision factors for both depot maintenance activities and product improvement programs. Furthermore, this study suggests that utilizing those common decision factors at the beginning stage, where constructive outcome would significantly grow.
Subject Guides: Veterinary Science Open Access Resources: Datasets, Databases and Repositories

This LibGuide provides information relevant to Veterinary Science open educational resources and open access
Experimental Realization of Finger Gesture Recognizing Glove Sensor for Deaf and Dumb Person

A majority of the human beings on this planet are deaf and dumb. The exchange of information between a deaf persons who knows sign language and the person doesn't poses a serious problem for them as compared to between who doesn't know the sign language. Since communication is the fundamental and one of the very important things to have in life therefore the person who doesn't know sign language feels alien in the atmosphere he lives in. Sign language is the non-verbal form of language which uses hand gestures to express feelings and to convey information and sign language is very popular among deaf community. This paper aim is to create a helping hand glove sensor for deaf people to communicate easily with other people. The glove has five flex sensors which are glued along lengths of five fingers on the glove. The glove produces a proportional change in resistance for every particular gesture. The analogue values which are the output of the sensors are converted into digital format. These gestures are analyzed using Arduino controller. This board compares the predefined voltage levels stored in the memory with the output of the flex sensor. And thus according to that a suitable match is found and a particular sentence is displayed on the LCD and also can be heard on the speaker. This is how the proposed sensor helps the deaf people to make their life easier than before and brings new colors to their life.
FEATURE EXTRACTION OF MOTOR IMAGERY EEG SIGNALS BASED ON MULTI-SCALE RECURRENCE PLOT AND SDA

When recognizing multi-class motor imagery electoencephalogram (EEG) signals directly using stacked denoising autoencoders (SDA), it is difficult to fully train the weights due to the small sample size, which results in poor classification effect.To overcome this problem, the multi-scale recurrence plot and SDA method are combined to extract features of multi-class motor imagery EEG signals for recognition.Firstly, multi-class motor imagery EEG signals are decomposed into a series of intrinsic mode functions (IMFs) with different scale by synchrosqueezed wavelet transform, and the recurrence plot of each IMF is constructed to form one-level feature data as input samples of SDA.Then, high-level abstract features which can better express category attributes are extracted from multi-scale recurrence plot by SDA.Finally, EEG signals are classified by using Softmax classifier.Four types of motor imagery EEG data of Datasets 2a in BCI Competition IV are used to verify the proposed method.The average classification accuracy is 0.89, which shows that the proposed method has good effectiveness and robustness.
PENGARUH MEDIA E-LEARNING DAN MOTIVASI BELAJAR TERHADAP IPK AKADEMIK MAHASISWA STKIP PANCA SAKTI

The purpose of the research is to examine the level of positive and significant (1) influence e-learning media to GPA of students in economic educationt program study year 2019/2020 in STKIP Panca Sakti, (2) influence learning motivation to academic GPA of students in economic educationt program study year 2019/2020 in STKIP Panca Sakti.The population of the research is students at economic educationt program study year 2019/2020 that amounts 697 students.The sampling technique used is the propotional random sampling, wich then obtained a sample of 255 students.Method of collecting data by using documentation and questionnaire.Data analysis method used descriptive analysis and multiple regression analysis.The result showed that (1) e-learning media significantly influence to academic GPA of students in economic educationt program study year 2019/2020 in STKIP Panca Sakti, (2) learning motivation significantly influence to academic GPA of students in economic educationt program study year 2019/2020 in STKIP Panca Sakti.
보육시설 종사자의 감정노동과 이직 및 잔류의도 관계에서 직무스트레스의 매개효과

Child care teachers play an important role in teaching basic life, physical exercise, communication, art experience, social relations, and natural inquiry as child care professionals in the development and growth process of infants and young children. The purpose of this study is to lower the turnover of childcare teachers and provide high-quality services to users by helping them to improve their welfare by improving their basic awareness and job stress of emotional labor.
Performance Prediction of Task Workloads in Work-Stealing Runtimes for NUMA Multi-core Architectures

Abstract: Work stealing is a popular load balancing technique which is successfully adapted by various user level task parallel runtime systems such as Cilk, TBB etc. On the other hand, processor manufacturers are working on releasing processors with more than one socket on chip, to overcome the memory wall problem. If work stealing based run-time systems are ported onto such multi-socket machines, it may lead to performance issues. This paper has attempted to study the impact of such multi-socket multi-core architectures on performance of work stealing based run-times. In this paper, a work stealing parameter called remote steal count is introduced specially for assessing work stealing run-times on multi-socket architectures. This paper also proposes a simple regression model between work stealing parameters and performance of task-based applications. This model is helpful to predict the performance impact of task parallel applications   while porting them into multi-socket hardware environment.
A multidisciplinary study for geothermal energy sources identification in the Baia Mare area (Romania)

&amp;lt;p&amp;gt;Geothermal energy is known as a renewable source that has little effect on environment, since no burning process is involved in the producing of thermal and electric energy. Geothermal water is considered an environmentally friendly energy source which is valuable especially in polluted areas. Our study area, the Baia Mare region, is located in the northwestern part of Romania, a region known as one of the most polluted environment in Romania due to its long-lasting local mining and metallurgical activities. Additional quantities of CO2 emissions resulted from the use of various, relatively cheap, heating sources by the local population. The main goals of our study are to evaluate the subsurface geothermal potential of the Baia Mare area and to identify promising geothermal exploitation sites. Heat flow values in this area are among the highest in Romania. We therefore plan to combine geological, geophysical, geochemical and hydrogeological data (geo-data) in order to provide a geoscientific solution for increasing the geothermal energy production in this part of Romania. Our research program contains surface geological mapping, geophysical surveys (active and passive seismic, magnetic, magnetotelluric and geothermal), geochemical analysis, hydrogeological surveys, modeling of geo-data and joint interpretation of geo-data. An initial 3D geothermal model will be built using existent geo-data. This model will help us to identify subsurface structures which show high potential for geothermal exploration. Interpretation of existent active seismic data collected during previous hydrocarbon exploration will provide information about the subsurface structural geology. The results of the new interpretation will be compared and correlated with the existent geological maps and sections for the study area. The magnetic data available in the public domain will be used to identify subsurface igneous bodies. The temperature data available from previous measurements will be used to build temperature-versus-depth distributions. These results will be analysed within a larger geodynamic framework. A pilot site will be selected after the analysis of the initial 3D geothermal model on which we plan to collect and record new geo-data. Data processing, inversion and modeling will be performed in order to create the final geothermal model with locations of promising exploitation wells.&amp;amp;#160;&amp;lt;/p&amp;gt;
Academic Collaboration between Eduard Pekarsky and Vladislav Kotvich in 1913–1934

У Д К 3
Review Of Cost Effectual Content Sharingin Cloud Environment

Cloud computing is a promising worldview that gives computing resources as a service over a system. Various information replication approaches have been introduced for information cloud in the previous decades. All replication method access a few qualities, for example, adaptation to internal failure, versatility, dependability, execution, stockpiling utilization, information access time and so on. Late examination permitted us to more readily comprehend the cost drivers and significant choices that can influence the costs related with moving to the cloud, to make the RAND Cloud Cost Model, and to build up a structure for contrasting the cloud and other data stockpiling and the executives’ options.
СУТНІСТЬ ПОНЯТТЯ ТА СКЛАДОВІ МЕНЕДЖМЕНТУ МІЖНАРОДНОЇ ОСВІТНЬОЇ ДІЯЛЬНОСТІ

The process of implementation of international educational activities should be based on the principles of: humanization, openness, accessibility of innovation, competitiveness, continuity, accessibility, where the effective management is a means. The management of international educational activities is considered as a relatively new phenomenon in terms of theoretically sound and experimentally tested technologies and systems for effective management of education and its structural components in the international context.
Autonomous Cars and Responsible Innovation

Digitalization, a dominant megatrend in today’s global world, offers numerous intriguing technological possibilities. Out of these novelties, self-driving cars have rapidly come to be a primary focus; the literature categorizes them as a radical innovation due to the possibility that the mass adoption of self-driving cars would not only radically change everyday life for members of industrialized societies, but calls into question the infrastructural, legal, and social ordering of towns and numerous aspects of transportation in the societies that adopt them. Meanwhile, the results of several international surveys with large samples show that public opinion of self-driving cars is ambivalent, indicating parallel signals of enthusiasm and concern. The aim of this paper is to develop key components of a general strategy for addressing the societal challenges associated with self-driving cars as identified in international surveys and relevant literature and using the framework of responsible innovation.
Finding Spoiler Bias in Tweets by Zero-shot Learning and Knowledge Distilling from Neural Text Simplification

Automatic detection of critical plot information in reviews of media items poses unique challenges to both social computing and computational linguistics. In this paper we propose to cast the problem of discovering spoiler bias in online discourse as a text simplification task. We conjecture that for an item-user pair, the simpler the user review we learn from an item summary the higher its likelihood to present a spoiler. Our neural model incorporates the advanced transformer network to rank the severity of a spoiler in user tweets. We constructed a sustainable high-quality movie dataset scraped from unsolicited review tweets and paired with a title summary and meta-data extracted from a movie specific domain. To a large extent, our quantitative and qualitative results weigh in on the performance impact of named entity presence in plot summaries. Pretrained on a split-and-rephrase corpus with knowledge distilled from English Wikipedia and fine-tuned on our movie dataset, our neural model shows to outperform both a language modeler and monolingual translation baselines.
Implementasi Algoritma K-Medoids Clustering Dalam Pengelompokan Angka Kelahiran Di Kota Pematang Siantar

Birth rate is an element of natural population growth. Birth is a term used in the demographic field to describe the number of children actually born alive. The high birth rate in Indonesia is still a major problem in population, population and environmental problems or the main problem of population in Indonesia, namely the number and population growth that is highly developed, population distribution, population age composition, and quality of population. To solve the problem that there is a method used in this study is the K-Medoids Clustering method, using 2 Clusters namely low Clusters and Clusters This study aims to determine the population density and to determine the birth of children each year based on the village. In this study using data mining techniques with the k-Medoids clustering method, the source of this data was obtained from the Office of Population and Civil Registration Pematangsiantar. Input data is data on the number of birth rates in 2015-2019 which consists of 53 villages divided into 2 clusters, namely low clusters and high clusters from the calculation of K-Medoids obtained as many as 43 villages as low clusters, 10 villages as high clusters. The implementation process using the RapidMinner 5.3 application is used to help find accurate values.
Zero-Shot Cross-Lingual Dependency Parsing through Contextual Embedding Transformation

Linear embedding transformation has been shown to be effective for zero-shot cross-lingual transfer tasks and achieve surprisingly promising results. However, cross-lingual embedding space mapping is usually studied in static word-level embeddings, where a space transformation is derived by aligning representations of translation pairs that are referred from dictionaries. We move further from this line and investigate a contextual embedding alignment approach which is sense-level and dictionary-free. To enhance the quality of the mapping, we also provide a deep view of properties of contextual embeddings, i.e., the anisotropy problem and its solution. Experiments on zero-shot dependency parsing through the concept-shared space built by our embedding transformation substantially outperform state-of-the-art methods using multilingual embeddings.
Expert System to Diagnose Diabetes Using Web-Based Fuzzy Mamdani Method: Expert System to Diagnose Diabetes Using Web-Based Fuzzy Mamdani Method

The aim of the system maker is to diagnose diabetes using a web-based fuzzy Mamdani method that is useful for detecting diabetes. Diabetes is also diabetes or diabetes. If the disease is not treated with proper treatment, it can cause various dangerous complications, and can even threaten the lives of sufferers. Implementation of an expert system to diagnose diabetes using web-based fuzzy mamdani aims to explore the symptoms displayed in the questions - questions in order to be able to diagnose various types of diabetes. This is from a research is a web-based expert system that can detect whether someone has diabetes what type. Based on testing the accuracy of the system, it can be concluded that with the fuzzy mamdani method is more accurate what type of diabetes. By using the PHP programming language with a MySQL database method the expert system used is fuzzy mamdani which is one part of the fuzzy inference system which is useful for drawing conclusions or the best decision in an uncertain problem, the Mamdani fuzzy concept is very flexible and has tolerance for inaccurate data based on language natural.
Cloud computing as a means of forming the educational environment of a higher educational institution

The article deals with the problems of the organization of the educational environment of higher educational institutions. The purpose of the article is to determine cloud computing as the most effective means of forming a unified educational environment of the university, providing a reliable organization of the educational process in the field of providing educational services in the “one window” mode in various social, political and economic conditions. Based on the analysis of modern platforms for organizing the educational environment and based on current trends in the IT market, Cloud Computing is currently one of the most promising areas. The article defines the essence of cloud computing, which is to provide hosting users with remote access to services, computing resources and applications over the Internet. Examples of the use of cloud technologies in the public sector and education are given. The main types of services provided by the Russian cloud services market (Saas and Iaas) are described. The implementation of the” National Cloud Platform O7″, developed by Rostelecom, is discussed in more detail. The advantages of organizing the educational environment with the help of cloud technologies are considered. Stand out. characteristic features of the Cloud Computing concept, various types of clouds are considered, their advantages and disadvantages. The organization of a unified educational environment of a higher educational institution through cloud computing is a promising direction that allows achieving high technological efficiency: while reducing the cost of purchasing special software and hardware, the quality and efficiency of the educational process in the conditions of digitalization of the economy significantly improves, and it also becomes possible to provide educational services in the “one window” mode, which is a priority of the Government of the Russian Federation.
Competitiveness Of Universities As A Priority Of Russian State Policy

The introduction of competition in higher education is due to high rates of modern changes, which include the need for rapid and effective adaptation to the changing requirements of the labour market; to the compliance with the requirements of science and technology; to the digitalization of education; to the constant updating and development of human capital.The purpose of this research is to analyze the relationship between state policy in higher education and increase the competitiveness of the Ural Federal University.Methods of collecting empirical data (analysis of documents); method of secondary data analysis of sociological research on the problems of Russian higher education; analysis of educational statistics of higher education; data analysis monitoring the effectiveness of Russian universities, and reports of the results of performances of the Ural Federal University were used in this study.The results are: the sense of competition and competitiveness in higher education, namely the quality of education, learning technologies and teaching methods, which presents the spectra of science is identified; the necessity of the improvement of the material base and infrastructure of universities is explained; the directions of improving the competitiveness of Russian universities and the legal framework of the implementation of state policy in the higher education of the Russian Federation are found.