Reviewerly/exHarmony huggingface dataset:
Practice-Oriented Approach to Training Tutors at the Siberian Federal University

The article demonstrates the possibilities of a practice-oriented approach to training tutors for the regional education system: such specialists are needed in the new social conditions of Siberia.The research is based on the empirical analysis of the educational services market for training tutors in Russia and the demands by regional employers for tutors.Indicators of successful training of tutors are their educational results achieved in accordance with the requirements of the Federal State Educational Standard of Higher Education and the professional standard of the tutor.Practice-oriented training of bachelors, coupled with varying the content of educational programs and increasing the share of practice and practical exercises, contributes to building up strategies for professional growth of future tutors, strengthening their adequate professional self-esteem and developing the personal traits required for a qualified specialist.The authors propose a new model of practiceoriented training of tutors, including their participation in educational events and professional tests during the university study period.The article describes the experience of Institute of Education, Psychology and Sociology at the Siberian Federal University in enhancing the practical component of vocational training, choosing teaching methods, their methodological support and innovative character of organizing student practices within the "Pedagogical Education (Tutor)" area of study.
AndroidX Test Library

A May 2018 Google I/O event announced the AndroidX open source project, which is used to develop, test, package, version, and release libraries within Android Jetpack. AndroidX replaces the Android Support Library. One of its major improvements is the fact that AndroidX packages are separately maintained and updated, so you can update AndroidX Libraries in your project independently.
A Re-look at the Introduction to Software Engineering Course

Jim Vallino has academic and industrial experience across a broad range of engineering disciplines.His academic training includes a B.E. in mechanical engineering, a M.S. in electrical and computer engineering, and after more than 16 years in industry, received a M.S. and Ph.D. in computer science.While in industry, he worked in small and large companies doing product development and industrial research.His responsibilities included both hardware and software development at AT&T Bell Laboratories, Siemens Corporate Research, and AVL, including microcode for a graphics processor, real-time medical image processing, and data acquisition and communications protocols for semiconductor process control.Since 1997, he has been a faculty member in Rochester Institute of Technology's Department of Software Engineering including the position of Department Chair.His professional interests are in the engineering of software for real-
Inclusion of Efficient Rules in PRISM Algorithm for Data Classification

Data classification is the process of classify data into different types, forms or any other separate classes.Data may be classified for a different of reasons, including ease of access, to observe with regulatory requirements, and to meet various other business or personal intention.In some cases, data classification is a regulatory requirement, as data must be searchable and recoverable within specified time durations.the focus of this paper is on the description of rule based classification and ensemble learning as well as the discussion on some existing methods and techniques.In our proposed approach we are using PRISM algorithm for rule induction.Based on induced rule, test data will be classified.In this paper we proposed Maximized the classification accuracy, Minimize the error rate and also Minimize the classification time.After that experimental evaluation will be performed with basic PRISM algorithm and will show comparative analysis of basic PRISM algorithm and other data classification algorithm such as SVM, Decision Tree, Perceptron Model and Logistic Regression.After comparing these classification algorithms, we found that Maximum accuracy using PRISM algorithm.
Phase-Based Nonrigid Deformation for Digital Subtraction Angiography

We present a method for digital subtraction angiography based on phase-based nonrigid deformation with specific consideration for changes between the image pairs. Input images are transformed into a scale-space representation using complex-valued filter responses. We apply a novel selection criterion to discern object motion and actual change by comparing the magnitudes in the responses. By manipulating phase, we directly generate a deformed image without explicit calculation of motion vectors. Our method is particularly useful in angiographic imaging where subtle changes between the image pairs should be preserved within the deformation and subtraction process. The experiments show that the proposed method preserves contrast for vessels and tumor stains while reducing motion artifact, which is clinically meaningful.
Improved PSO Algorithm for Training of Neural Network in Co-design Architecture

This paper proposes a new version of the standard particle swarm optimization (SPSO) algorithm to train a neural network (NN).The improved PSO, called the wPSOd -CV algorithm, is the improved version of the PSOd -CV algorithm presented in a previous study.The wPSOd -CV algorithm is introduced to solve the issue of premature convergence of the SPSO algorithm.The proposed wPSOd -CV algorithm is used in a co-design architecture.Experimental results confirmed the effectiveness of the NN trained by the wPSOd -CV algorithm when compared with the NN trained by the SPSO algorithm and the PSOd -CV algorithm concerning the minimum learning error and the recognition rates.
ANALYSIS OF THE USE OF CELLULAR OPERATORS USING THE ANALYTIC HIERARCHY PROCESS METHOD

The development of technology in the telecommunications sector is now easier to be enjoyed by the community. Almost all regions have been able to enjoy the ease of access to information through telecommunications networks. Telecommunications service providers certainly have competed in such a way as to be able to hold users to remain loyal to the provider used. From several surveys conducted, there are still many users who cannot be loyal to use the services of these providers. The increasing number of communication network providers makes users more choices. Various ways are carried out by communication network providers to maintain their users such as giving bonuses, providing cheap rates, increasing services to the regions. In this study will focus on the level of customer satisfaction with cellular operators with a variety of criteria that have been prepared which will be a consideration for users in using these cellular operators. This research will use the AHP method (Analytic Hierarchy Process) to find out which cellular operators are the most superior based on the judgment of the user with various criteria each. So that in the end it will be known which cellular operators will be selected and purchased by consumers according to their respective needs. The results of this study show that based on the bonus, IM3 is the best with a weight of 0.21712. Then based on the price rate, a tri card with a weight of 0.16565. Furthermore, the service criteria show a better Sympathy card with a weight of 0.21311
Engineering Scalable Distributed Environments and Organizations for MAS

In MAS programming and engineering, the environment and the organisation can be exploited as first-class design and programming abstractions besides the agent one. A main example of a platform implementing this view is JaCaMo, which allows the programming of a MAS in terms of an organisation of cognitive agents sharing a common artifact-based environment. However, MAS models and platforms in general do not provide a satisfactory approach for MAS developers to uniformly deal with distribution at multiple dimensions -- agent, environment, and organisation. Typically, environments are either centralised in a single node, or composed by parts that run on different nodes but with a poor support at the programming and execution levels to deal with that. In this paper, we tackle this problem by proposing a model for engineering world-wide distributed environments and organisations for MAS. The approach integrates the A&A (Agents and Artifacts) conceptual model with a web/resource-oriented view of distributed systems as proposed by the REST architectural style. To evaluate the approach, an extension of the JaCaMo open-source platform has been developed implementing the proposed model.
Research Review and Prospect of Fault Diagnosis Method of Satellite Power System Based on Machine Learning

Aiming at the complex characteristics of the current satellite power supply system and the mass data produced in its operation process, an integrated fault diagnosis method based on deep learning and expert diagnosis was proposed. The deep learning has the capability to deeply investigate the incidence relation between abnormal data and faults, and the has the superiority of making full use of domain expertsâ€™ experience and simulating their reasoning process expert system es for solutions. The combination of them both can improve the reliability of satellite power failure diagnosis and provide a new way of thinking for the development of satellite power failure diagnosis method.
Improving Speaking Performance Through Pecha Kucha Presentation Method

The objective of this research is to show the improvement of the students’ speaking performance using Pecha Kucha presentation method among the tenth graders of SMA Muhammadiyah East Lampung. The research method used in this research is a Classroom Action Research (CAR) which is used to solve the students’ problem in speaking performance. The subjects of this research are X MIA students of SMA Muhammadiyah Pekalongan East Lampung in the academic year of 2017/2018. The research instruments used to collect the data in this research are test, observation and documentation. The result of this research shows that the implementation of Pecha Kucha presentation method is successful since the criteria of success are achieved. The first criterion is 70% of the students could pass the target score ≥ 70 based on the KKM. The finding shows that 77.78% of the students had already achieved the target score. Besides, the second criterion is the students who became more active in the learning process. The result of observation shows that by using Pecha Kucha presentation method, most of the students are involved actively in the learning process.
On the Talent vs. Luck-Based Evaluation of the Classification Process

Performance measures of classification algorithms play a crucial role in the evaluation of the learned models. Nevertheless, the vast majority of such measures are based on the same notion of classification performance, i.e., the ability of the classifier to recognize data samples from predefined training and testing sets. In this paper, we aim at introducing a new framework of evaluation of the classification process based not only on the aforementioned ability (“Talent” of the classifier) but also on randomness (“Luck”) that would affect its performance. Based on the studies with socio-economic contexts where “Luck” has been shown to play a crucial role in success and failure, we define a new measure to quantify the Talent versus Luck (TvL) tradeoff within a classification framework and prove its relationship with the generalization error. The proposed measure is validated via convolutional neural networks both with and without dropout layer, in order to highlight the relation of the measure to the generalization aspect, using the MNIST dataset. The experimental results confirm the fundamental role of TvL tradeoff in the evaluation of classifiers and in selecting the most “successful” ones suggesting the TvL measure as a new, useful tool in the arsenal of evaluation of the classification process.
PEMBUATAN E-KATALOG PRODUK DI FACEBOOK SEBAGAI SARANA PROMOSI UNTUK MENINGKATKAN PENJUALAN DENGAN MENGGUNAKAN APLIKASI PAINT TOOL SAI DAN ADOBE PHOTOSHOP DI RESTO AYAM BACEM BAKAR GRIBIG MALANG

This research aims to develop promotional media in the form of e-catalog that will be applied to the company Resto Ayam Bacem Bakar Gribig. The method used an Action Research method consisting of planning, action, observation, an reflection. The method to collect the data an observations, interviews, documentation and questionnaires. The finished design of e-catalog was then evaluated by spreading the questionnares to 2 computer experts, 2 marketing experts, and 8 potential users. The measurement of the design development affectiveness was measured by EPIC Method (Empathy, Persuasion, Impact, Communication). The results of questionnaires from respondents stated that the score of Empathy dimension was 4.15, Persuasion dimension was 3.9, Impact dimension was 4.2, and Communication dimension was 4.3. With an overall average of EPIC Rate was 4.13 it can be stated that the e-catalog was very effective. The result of this research indicated that the e-catalog is feasible to be as a promotional media in Resto Ayam Bacem Bakar Gribig. It is expected that the e-catalog can be used and help Resto Ayam Bacem BakarGribig in promote its service products.
Simultaneous one-shot profilometry and gamma correction

We propose a method to correct the nonlinearities introduced by the projector and camera system in one-shot fringes projection profilometry. It is shown that the gamma value can be calculated with high precision employing Fourier techniques. Fourier and phase shifting phase extraction experiments are carried out to show the applicability of the method.
Text Template Mining using Named Entity Recognition

In this paper, the named entity recognition system is built using morphological, lexical and semantic analysis.Rule based system is designed for template mining from the Arabic text.Arabic texts are selected from oil production domain.They are taken from Arabic BBC, RT and CNN websites.The System is tested on these texts and the results give high performance, less error made and good accuracy in finding the templates from texts according to named entities extracted.
Design and Development of Web Service Application for Multi-Bank Student Payment System in State University of Jakarta

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The Application of VR Technology in the Construction of Learning Resources of Mobile Application Platform

with the development of science and technology, three dimensional (3D) computer interaction, virtual reality and other technologies are used to improve the form of teaching demonstration and create an interactive teaching platform for illusion, so that the teaching effect can be greatly improved. Based on the design and implementation of illusion teaching platform under the Unity3D digital three-dimensional interactive technology, 3Dmax software is used to construct the 3D virtual learning scene of the and the 3D model of contradictory space, an important content of Unity3D is used as a development platform for implementing functions such as virtual roaming and human-computer interaction. The technical methods and key technologies of digital interactive teaching are discussed, and the most effective illusion teaching platform is built. Finally, the completed illusion teaching platform – visual illusion 3D interactive learning system is systematically tested and analyzed from the aspects of software performance and application effect. The results show that the illusion teaching platform with virtual reality technology achieves the expected effect well, and the use of this teaching platform can improve students' ability to understand and apply the teaching content of visual illusion.
Fuzzy-Neural-Network Based Audio-Visual Fusion for Speech Recognition

Speech recognition is an important classification problem in signal processing. Its performance is easily affected by noisy environment due to movements of desks, door slams, etc. To solve the problem, a fuzzy-neural-network based audio-visual fusion is proposed in this study. Since human speech perception is bimodal, the input features include both audio and image information. In the fuzzy-neural-network, type-2 fuzzy sets are used in the antecedent parts to deal with the noisy data. Furthermore, a linear-discriminant-analysis (LDA) is applied in to the consequent parts to increase the “discriminability”. Compared with pure audio-based speech recognition, the fuzzy-neural-network based audio-visual fusion method is more robust in noisy environment.
The Blockchain As A Digital Technological Platform For Electronic Government Development

As part of this study, Blockchain is considered as an integrated-distributed technology and a digital platform for transformation and development of e-government structures. There is conducted critical assessment of Blockchain technological characteristics and also, there are considered the consequences of its implementation into government organizations and their processes. At the same time, from the interdisciplinary point of view, it is regarded to transfer from a technology-oriented approach to a needs-oriented approach, which is adapted to Blockchain applications, ensuring and keeping the requirements for administrative and managerial processes. Based on the assessment, the authors’ substance the approach to investing the potential benefits of using Blockchain for e-government structures, as well as managing the architecture and applications of Blockchain in accordance with social needs and social values within the changing institutional paradigm conditioned upon the transition to a digital economy. On the one hand, the prospect of Blockchain technology management, in which government agencies use Blockchain technology for their own processes, such as the provision of public and municipal services, where Blockchain technology is used to manage transactions. Another perspective is called Blockchain technology management, which defines how the Blockchain should look like, how to adapt to changes and ensure the ability to implement the goals and objectives of public authorities, as well as the social needs of the population.
Compressed filesystem for managing large genome collections

Abstract Motivation Genome repositories are growing faster than our storage capacities, challenging our ability to store, transmit, process and analyze them. While genomes are not very compressible individually, those repositories usually contain myriads of genomes or genome reads of the same species, thereby creating opportunities for orders-of-magnitude compression by exploiting inter-genome similarities. A useful compression system, however, cannot be only usable for archival, but it must allow direct access to the sequences, ideally in transparent form so that applications do not need to be rewritten. Results We present a highly compressed filesystem that specializes in storing large collections of genomes and reads. The system obtains orders-of-magnitude compression by using Relative Lempel-Ziv, which exploits the high similarities between genomes of the same species. The filesystem transparently stores the files in compressed form, intervening the system calls of the applications without the need to modify them. A client/server variant of the system stores the compressed files in a server, while the client’s filesystem transparently retrieves and updates the data from the server. The data between client and server are also transferred in compressed form, which saves an order of magnitude network time. Availability and implementation The C++ source code of our implementation is available for download in https://github.com/vsepulve/relz_fs.
Visual and Text Sentiment Analysis

he information on text has been analysed rigorously in several areas pertaining to business decision-making (Miller et al. in Sentiment flow through hyperlink networks, pp 550–553, 2011, [1]). A tweet for images is shown in Fig. 5.1. The visual information analysis covering information retrieval from images has not made much progress relatively. Several studies have suggested that more than one-third of social blogs’ data are images.
CRYPTOCURRENCIES - A NEW MODEL OF BUSINESS

The development of technology has led to the creation of new phenomena in the financial world.One of these phenomena is crypt, digitally decentralized currencies created for the "world of
Database Classification of MPEG7 Shape Using Rotation Moments and Generated Stationary Transformed Features

After the main trellis processing, the final score will contain all matching information. The graph matching shape classification is also used, where the Extracted Stationary Transformed Features is used to describe the Gabor graph for signal Rotation Invariant Moments object. The difference between our work and theirs is that we use feature point’s as graph node values and they use Shape Database Classification Gabor jet. Another difference is that and they didn’t use to do the graph matching.
Artificial intelligence for software development — the present and the challenges for the future

Since the time when first CASE (Computer-Aided Software Engineering) methods and tools were developed, little has been done in the area of automated creation of code. CASE tools support a software engineer in creation the system structure, in defining interfaces and relationships between software modules and, after the code has been written, in performing testing tasks on different levels of detail. Writing code is still the task of a skilled human, which makes the whole software development a costly and error-prone process. It seems that recent advances in AI area, particularly in deep learning methods, may considerably improve the matters. The paper presents an extensive survey of recent work and achievements in this area reported in the literature, both from the theoretical branch of research and from engineer-oriented approaches. Then, some challenges for the future work are proposed, classified into Full AI, Assisted AI and Supplementary AI research fields. Keywords: software development, artificial intelligence, machine learning, automated code generation
Terminological Information Extraction from Russian Scientific Texts: Methods and Applications

Scientific texts contain a lot of special terms, which together with their definitions present an important part of scientific knowledge to be extract- ed for various applications, such as text summarization, construction of glossaries and ontologies and so on. The paper reports rule-based methods developed for extracting terminological information involving recognition of term definitions, as well as detection of term occurrences within scientific or technical texts. In contrast to corpus-based terminology extraction, the developed methods are oriented to processing a single text and are based on lexico-syntactic patterns and rules representing specific linguistic information about terms in scientific texts. The formal language LSPL for specification of the patterns and rules is briefly characterized, which is supported with programming tools and used for information extraction. Two applications of the methods are discussed: formation of glossary for a given text document and subject index construction. For these applications, both collections of LSPL patterns and extraction strategies are described, and results of their experimental evaluation are given.