Reviewerly/exHarmony huggingface dataset:
A Context-Aware Variational Auto-Encoder Model for Text Generation

Although text generation models based on the theme have achieved good results, it may not be associated with the context, for it does not take the relationship between the current word and the possible forthcoming words into account. To solve this problem, we propose a new text generation model called context-aware variational auto-encoder. The context-aware VAE model predicts that the next word takes into account the impact of previous information. Our model also considers the forthcoming words in the text generation process. Experimental results demonstrate that our model gained a significant effect on contextual text generation. On the one hand, it outperforms the baseline on context-sensitivity in the cloze task accuracy experiments. On the other hand, the model is also better than the baseline model in terms of language expression ability.
Design Of Mobile-base Bali Regional Food Crops Recommendation Information System

Abstract&#x0D; Plant food is a necessary staple of each human being, in the process of cultivation is often the case things are not in want as failed harvests. These problems are caused by various factors such as weather that is not suitable for the needs of the plant or environmental conditions that are not suitable for its growth. Based on the problem that it takes a system of information that can provide information about the needs of that required by a plant food from the weather and environment of his life. The article will discuss the design of the application system of information on food crops to the area of Bali -based applications mobile.&#x0D; Keywords: Applications, Mobile, Information Systems, Food Crops, Weather, Environmental Conditions.
RESEARCH OF PROFESSIONAL MOTIVATION OF UNIVERSITY STUDENTS

This article is devoted to one of the most urgent problems of modern students –professional motivation, which significantly affects the future activity of a specialist. Features of formation of professional motivation of students in the course of educational activity in higher education are considered.In turn, professional motivation is an internal driving force that encourages you to develop yourself as a person, master and improve your professionalism. Questions are put forward about what its significance is for the student and how it should be formed in the educational process.The empirical study was conducted on the basis of the Abay Kazakh national pedagogical University. The study involved78 1st-year students of the Institute of pedagogy and psychology. Diagnostic tools were used to assess the formation of students ' professional motivation.The program of empirical research included the results of the following methods: "Research of motivation of professional activity " by K. Zamfir (modified by A. A. Rean) and " Determination of motivation to study" by V. G. Katashev. The results of the analysis revealed high and low levels of professional motivation. Based on the generalization of research data, the author analyzes the features of the emergence and development of professional motivation of students during the training period
LSC-North Harris Library Research Guides: Library Online Learning Modules: STEM Modules

This guide is to serve as a menu of instruction modules to meet the information literacy needs LSC-NH online classes. Each module can be embedded into D2L, and takes 5-10 minutes to complete.
Library System and Services during COVID-19 Outbreak Throughout the Globe: Issues, Challenges and Strategies

This assessment includes the distinctive library system and organizations during Coronavirus scene. Its also sees the help work that library system and organizations are taken up. Its thoughts the amount of automated organizations stage open rest of the world. It moreover progresses the impact and use of casual correspondence districts. The library structure and organizations are support the entire the neighborhood their scholarly activities. The central piece of library and library organizations is to thought down information as indicated by the customer responsibility, task as an information disseminator and relationship of data through the distinctive information gadgets. The library structure and organizations are show their knowledge with the guide of execution despite the various capacities is need of the customers. The library organizations can give E-Journals, E-books, E-substance, information joins and their customer organizations. Similarly as the outcome of library structure and organizations describes the whole neighborhood strategy for the accept care of position and gets precise information in the during Coronavirus pandemic condition. The assessment helps the library customer and staff to improve their endeavor set by the difficulties and serve the information like a careful bunch of the country
GeomCA: Geometric Evaluation of Data Representations

Evaluating the quality of learned representations without relying on a downstream task remains one of the challenges in representation learning. In this work, we present Geometric Component Analysis (GeomCA) algorithm that evaluates representation spaces based on their geometric and topological properties. GeomCA can be applied to representations of any dimension, independently of the model that generated them. We demonstrate its applicability by analyzing representations obtained from a variety of scenarios, such as contrastive learning models, generative models and supervised learning models.
Teknologi Informasi Dalam Pendidikan

Abstract: The development of technology at this time has entered the realm of the world of education, various forms of technological progress in the world of education can be accessed easily and whenever used to be used. Formerly difficult things to do now can be easily obtained, examples such as reading books, we no longer need to go to the library to buy books or buy books to be able to read books, we just open the smartphone we have and access via the internet by opening an E-book or electronic books. Not only that, the convenience provided with today's technology makes technology users spoiled, for example as we are currently being attacked by the covid-19 virus outbreak that supports us having to open the crowd for now as stated by the health protocol currently. However, with technology we can study at home and still be able to interact with friends and teachers, only with dakam, videos called online or online learning systems. Keywords : Education, Tecnology, Information
Testing UNFC as a harmonized supporting tool for resource management in Europe

&amp;lt;p&amp;gt;With the global increase in raw material demand comes the need for harmonized supporting tools for sustainable resource management in Europe. Europe needs to assess their resource potential, but the European countries do not have a common tool to aggregate information for continent-wide resource inventories. The United Nations Framework Classification for Resources (UNFC) is a system that may be used for this purpose.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;One of the specific tasks in the MINTELL4EU project under the GeoERA programme is to test if the European geological surveys will be able to use UNFC as a tool to evaluate a country&amp;amp;#8217;s known and potential resources across variable levels of knowledge. The project will also show, if the application of UNFC can provide better harmonization of mineral resource data nationally and across Europe.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The work on UNFC in MINTELL4EU is based on case studies to gain experience. Based on the knowledge and lessons learned from the case studies, guidelines and recommendations for further work will be given. Preliminary results show that there is a need for a more harmonized system and that stricter guidelines are required. On top of this, there are different levels of experience in UNFC among the European geological surveys, and the approach and methods on UNFC varies between the countries.&amp;lt;/p&amp;gt;
DEVELOPMENT OF COMPETENCE OF FUTURE SPECIALISTS IN CONDITIONS OF INCLUSIVE EDUCATION

The article discusses the ways, directions and features of developing the competencies of future specialists in inclusive education. The research analyzed the research and works of a number of foreign scientists dealing with competence issues, including the research of Kazakh scientists who contributed to the development of professional training, contributed to the solution of the problem. To reveal the essence and content of competence, the concepts of "professional competence of a teacher", "inclusive competence" and "professional competence" in various aspects were considered in depth. On the basis of various data, the possibilities of using innovative technologies, active methods and tools used to develop the competencies of a future specialist in the process of inclusive education are investigated. It is based on some data related to the research problem. The concept of competence is the responsibility and ability of the future specialist to their actions.
DESIGN OF THE DISTANCE LEARNING MODEL IN SECONDARY SCHOOLS OF THE REPUBLIC OF KAZAKHSTAN

The article discusses a comprehensive model of distance learning in secondary schools of the Republic of Kazakhstan, based on the creation of quality educational content in accordance with the basic requirements of updated education content; distance format of technologies for the criterion assessment of educational achievements of students; psychological and pedagogical support of students in the conditions of distance learning; technical equipment of students in the conditions of preschool.The results were obtained through a sociological study to monitor the status and diagnosis of psychological and pedagogical problems in the educational process of secondary schools in the Zhambylregion. The presented model of education in the conditions of DLT is based on the development of modern infrastructure for the development of modern digital and comfortable educational environment; design of the educational process based on the segmentation of the school contingent; application of criterion assessment technology; creation of digital educational resources; development of educational resources for teachers; creation of educational programs for teachers in the region. The implementation of the proposed training model will make it possible to create an educational space providing for the individualisation of educational trajectories and favourable conditions for interaction between students and teachers, productive learning of curricula, achievement of meta-subject results and improvement of information competence among schoolchildren.
International Magazine Archive

International Magazine Archive Index journals. It is aiming at rapid evaluation and Indexing of all local and international journals.International Magazine Archive provides following services with Frequency of 12-Indexing round per year:Evaluation and Indexing of journalsEstimation quality of journals based on comprehensive defined standards.journal panel for journal to monitor and control quality of their journals.
Research on super-resolution reconstruction of single frame image oriented to multi-type semantics

Images with low resolution and fuzzy semantics will have a negative impact on subsequent tasks such as object detection and behavior prediction. Therefore, it is particularly important to improve the resolution of the image. Compared with the existing three types of resolution reconstruction methods, the convolutional neural network super-resolution technology (SRCNN) that emerged in 2014 has greatly improved the restoration accuracy. However, the model still has the problem of poor convergence performance when processing multi-type semantic image reconstruction. Aiming at network optimization, this paper proposes an IPSO-SRCNN model, which initialize the network weights by using the Improved Particle Swarm Optimization (IPSO) and modify the weights by combining the gradient descent (GD) method, so that the IPSO's global search capability and the GD's local search ability can be fused. This paper designs three experimental modules and compares with five reconstruction methods to verify the reliability and practicability of the proposed model on the one hand. On the other hand, it highlights the potential of the proposed model for the reconstruction of multi-scene semantics.
Containerization on Petascale HPC Clusters

UT Austin-Portugal Program, a collaboration between the Portuguese Foundation of Science and Technology and the University of Texas at Austin, award UTA18-001217
Random Forests with Optimized Leaves for Hough-Voting

Random forest-based Hough-voting techniques are important in numerous computer vision problems such as pose estimation and gesture recognition. Particularly, the voting weights of leaf nodes in random forests have a big impact on performance. We propose to improve Hough-voting with random forests by learning optimized weights of leaf nodes during training. We have investigated two ways for the leaf weight optimization problem by either applying L2 constraints or L0 constraints to those weights. We show that with additional L0 constraints, we are able to simultaneously obtain optimized leaf weights and prune unreliable leaf nodes in the forests, but with additional costs of more computational costs involved during training. We have applied the proposed algorithms to a number of different problems in computer vision, including hand pose estimation, head pose estimation, and hand gesture recognition. The experimental results show that with L2-regularization, regression and classification accuracy are improved considerably. Further, with L0-regularization, many unreliable leaf nodes are suppressed and the tree structure is compressed considerably, while the performance is still comparable to L2-regularization.
Security Analysis of a Robust Lightweight Algorithm for Securing Data in Internet of Things Networks

Recently, the amount of important information and the tremendous sensitivity generated by the interconnectedness of millions of devices (embedded, wireless sensing, radio frequency identification) which are heterogeneous through promising such modern technologies as the IoT. In fact, these small computerized devices have limited capabilities of resources. Therefore, there is an extremely and dire need to protect and secure the sensitive data that generated by these devices taking into account their limited capabilities. However, the traditional coding algorithms like (AES and RSA) are not appropriate for these resource-limited devices due to their high computation cost and large memory consumption. In addition, the integrity and security of data should not be compromised by designing a simple encryption algorithm. Thus, a robust lightweight algorithm for encoding 64-bit data for an 80-bit key is suggested in this paper to provide high hardware security in just six rounds and work on a combination of Feistel and SP architectural methods to increase the encoding complexity. The suggested algorithm is simulated by FELICS and Matlab tools. Different data types such as text and images are used to implement this algorithm. The simulation results show the superiority of the proposed algorithm in different aspects as security, performance, and complexity.
The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning

In this work we develop a quantum field theory formalism for deep learning, where input signals are encoded in Gaussian states, a generalization of Gaussian processes which encode the agent's uncertainty about the input signal. We show how to represent linear and non-linear layers as unitary quantum gates, and interpret the fundamental excitations of the quantum model as particles, dubbed ``Hintons''. On top of opening a new perspective and techniques for studying neural networks, the quantum formulation is well suited for optical quantum computing, and provides quantum deformations of neural networks that can be run efficiently on those devices. Finally, we discuss a semi-classical limit of the quantum deformed models which is amenable to classical simulation.
Research Guides: Tips for Using Library Search: Catalog Search Features for Mirlyn Classic Users

Provides some tips and strategies for effectively using the University of Michigan Library search engine.
THE ROLE OF COOPERATIVE LEARNINGTECHNOLOGYIN INTENSIFICATION BIOLOGY EDUCATION

This article addresses the role of cooperative learning technology in intensifying the process of teaching general biology. Among the diversity of pedagogical technologies, the most relevant to the aims of education is cooperative learning technology.In addition, the authors analysed the content, timing, density of the training and considered the most effective methods of integrating this technology into the educational process, as well as a review of domestic and foreign literature for the same purpose. The survey revealed that one of the main problems of the modern education system is the intensification of the educational process. Thus, the main task of intensifying the teaching of general biology is to increase its relevance, motivation and content, increase the intensity of training activities, develop the mastery of educational organization, development and introduction of new methods and forms of educational work.
지식재산권법에 의한 빅데이터의 보호

With the fourth industrial revolution represented by IoT, big data analysis and AI, the value of big data is increasing, and promoting the appropriate use of such big data is a key to increase the growth potential of each country. In order to promote the active market distribution of big data, it is essential to develop an appropriate system that data providers and users can provide and utilize data without anxiety, and thus, it is necessary to discuss how to protect big data through the current intellectual property rights or future legislation.Countries focusing on the value of big data are already showing a variety of moves. First, the European Union grants “sui generis” database right to protect specific databases for which substantial investments have been made. On the other hand, in the United States, data is protected by not exclusive monopoly rights but passive protection through unfair competition prevention. Also, in Japan, two major legal revisions have recently been made in connection with big data protection, namely, revision of the Unfair Competition Prevention Act, which introduces a new provision for protecting big data, and revision of the Copyright Act, which establishes flexible right restriction provisions corresponding to the development of digitization and networking both in May 2018.Of course, big data may receive certain legal protection under the current Korean intellectual property law such as patent law and copyright law, but it seems to have some limitations. In particular, although the revision of the Korean Copyright Act in 2003 introduced a provision to protect the database under the copyright law, questions have been raised as to whether it is really appropriate to protect database by exclusive rights through copyright law. In addition, the trade secrets that many companies are actually using to protect big data is outside the scope of the discussion of the new protection of big data, which aims to promote the release and distribution of data.On the other hand, the method of including big data in new protection targets of the Unfair Competition Prevention Act may be a more likely approach. The Unfair Competition Prevention Act grants only passive protection and is the most flexible legal system to include newly emerged objects in the scope of protection. The possibility of implementation is high because it will be able to avoid expected large-scale oppositions in the case of introducing exclusive monopoly rights, and it will also be able to respond flexibly even at the stage of specific enforcement. It is necessary to make continuous discussions on the most appropriate protection methods that can achieve the dual goals of Payback on big data production and Free circulation of information
An Overview of Blockchain Technology for Agro Transaction

Public administration across worldwide with much increased resources demands transparency and security. As many countries started adopting smart city concepts, new technologies should be utilized to protect the several public administration services against corruption, intruders rendering active role and transparency for the public. The existing challenge of gaining trust, elimination of corruption can be achieved by integration of blockchain technology for the public administration process. The farmer personal, sensitive information’s are protected using Proof of Work (PoW) concept. Smart contracts can be utilized for the governmental subsidy money distribution to the farmers providing privacy preserving. This smart contracts can be helpful in eliminating over billing, money mishandling. The transparency is achieved by using hyperledger concept. To our knowledge this work is first public Blockchain based experimental approach for public administration compared with the theoretical approaches.  This work study examines the impact of blockchain technology in agriculture benefiting the farmers eliminating the mediators, agents
Private Cloud Storage for Organization Using Microsoft Azure

Cloud storage is the file storage in the cloud(online). Basically, in any applications the data  is stored in a local hard drive, external hard drives, or flash drives,  The applications like Cloud storage makes data to store online called cloud .In this proposal  cloud storage services are used for the local drives which are operated at low disk space. This application is implemented to stream music files, text files, video files which could be uploaded from anywhere. The files could be secured with password and encryption.The main advantages of this implementation is secured backup data , easy sharing and access of data like phone , tablet or another computer.
Cloud Based Stock Price Prediction Using News Sentiment Analysis

Stock price prediction is a difficult task, since it very depending on the demand of the stock, and there is no certain variable that can precisely predict the demand of one stock each day. However, Efficient Market Hypothesis (EMH) said that stock price also depends on new information significantly. One of many information sources is people’s opinion in social media. People’s opinion about products from certain companies may determine the company’s reputation and thus affecting people’s decision to buy the stock of the company. When using opinion as primary data, it is necessary to make a suitable analysis of it. A famous example using opinion as data is sentiment analysis. Sentiment analysis is a process to determine emotion/feeling within people opinion about something, in this case products of some companies. There are some researchers about sentiment analysis used to predict the stock prices. Bollen on his research concludes that people opinion on social media such as Twitter can predict DJIA value with 87.6 percent accuracy. This shows that there is a relation between sentiment analysis and stock prices. Our purpose on this research is to predict the Indonesian stock market using simple sentiment analysis. Naive Bayes and Random Forest algorithm are used to classify tweet to calculate sentiment regarding a company. The results of sentiment analysis are used to predict the company stock price. We use linear regression method to build the prediction model. Our experiment shows that prediction models using previous stock price and hybrid feature as predictor gives the best prediction with 0.9989 and 0.9983 coefficient of determination.