Reviewerly/exHarmony huggingface dataset:
Aportes instrumentales y sustantivos de Blockchain a la educación

Blockchain breaks into the educational scenario offering alternatives for improvement over certain administrative processes, such as recognition of user identity, non-mediated validation of academic certificates, or the use of smart contracts, among other novelties. Futuristic chronicles predict a transformation of the architecture of the educational system as a whole and an unprecedented synergy between teachers, institutions and formal and non-formal areas of education. Although the advances are in their infancy and there isn’t much academic research on the subject yet, it is clear that Blockchain has great potential with regards to its administrative application. Some educational initiatives based on the model of multilateral technological platforms result to be interesting as well as challenging. It is necessary to warn, however, about the little contribution that the application of Blockchain technology entails in the pedagogical dimension, and about the uncertainty that hangs over the revolutionary claims of the most extreme prospects, which predict more transformative power than what the technology itself seems to offer.
TweetGST: A Web Based Systems for Sentiment Analysis and Opinion Mining for GST in Malaysia

Abstract Twitter is one of the most used platform for communication by people around the world. Sentiment analysis and opinion mining on twitter has become an important field of research that sees beyond the number of likes, shares and comments that users have for some topics. Nowadays, business organizations are not aware of emotional aspect of their customers and may take longer time in analyzing the market sentiment in making the necessary business decision. TweetGST is a web based system that enable business user to extract GST based tweets from Twitter as well as it helps in analyzing the tweets accordingly. TweetGST enables for trend analysis and sentiment analysis to be made. These analysis will help the business organization in order to understand customer sentiment and provide for their needs. The analyzed tweets will be used in helping the business organization to make the right decision which are recommendation for sales and stocks. Thus, TweetGST is expected to increase the revenue of the businesses.
Overview of generalized algebraic data types in OCaml

The introduction of generalized algebraic data types (GADTs) extend algebraic datatypes by allowing type constructor abstraction and polymorphism, which results in numerous applications like embedding domain-specific languages, generic programming, dependently-typed programming and implementing typed intermediate languages. In this project, I look into various applications of GADTs in order to understand its usage and benefits. We also mention our experience while using them in practice.
Book Monitoring System / Kitap Takip Sistemi

The project was prepared by the Ministry of National Education for free of charge to students, and the students were given full and timely deliveries, and the problems were reduced and books were prevented. In the meetings held with Provincial and District Directorates of National Education, the idea of planning the books in place in the districts and schools where the number of e-school students were planned while distributing the books to the districts was emphasized. In the present application, distribution, distribution and removal of books according to demand. The number of current students in the distribution to our application can be seen on the basis of the organization and the distribution is planned according to this list. Students are expected to be transported and will be able to arrive at the books that have been updated. We will ensure that the delivery documents are linked to the system and followed up. Where the books in provinces and districts are high, the numbers to be requested from the ministry will be minimized. If the project is successful, there will be no public harm to be prevented from falling into the idle state of the books.
Vibroacoustic monitoring and troubleshooting of the stators of turbogenerators

The essence of resource-saving technology of turbogenerators operation is to reduce the intensity of vibro-impact processes in defective mounting attachment up to their full blocking by changing the operating parameters of the generator, which do not affect the output of active power. The results on the example of 8 turbogenerators of thermal power plant are shown. It can be seen that the power of vibro-impact processes, and, therefore, the intensity of wear of the stator elements can be significantly reduced in most of the turbogenerators of this station.
The Use of Intra Prediction Method in Wavelet-Based Video Coding Systems

Modern image and video compression technologies include both lossless compression methods, such as entropy coding, Inter-frame and Intra-frame coding, and lossy compression methods, such as discrete orthogonal transforms with quantization. All these techniques are actively applied in video codecs based on the H.264 and H.265 standards. Discrete wavelet transform (DWT) is one of the most perspective versions of discrete orthogonal transforms. Both Intra-frame coding and wavelet decomposition of images allow to reduce the volume of transmitted data, but they are not used together in video coding systems. The combined usage of these methods seems to be a promising approach in terms of visual data compression. Thereby the aim of this research is to develop a new technique based on the combination of Intra-frame coding and the DWT and to test the applicability of the proposed method in the image compression tasks. The effectiveness of various implementations of the proposed algorithm, including those based on contexts and using several levels of wavelet decomposition of images, was evaluated in the study.
Sub-band Vector Quantized Variational AutoEncoder for Spectral Envelope Quantization

Recently, a lot of deep learning model successful in taking over conventional methods in speech processing fields. Vector quantization is a popular technique to reduce the amount of speech data before transmitting. The conventional vector quantization method is based on the mathematical model. Last few years, the Vector Quantized Variational AutoEncoder has been proposed for an end-to-end vector quantization based on deep learning techniques. In this paper, we investigate the sub-band quantization in the Vector Quantized Variational AutoEncoder. This model can concentrate on specific frequency bands to assign more bits and leave the unnecessary band with few bits. Experimental results show the efficiency of the proposed quantization method for the spectral envelope parameters of the high-quality vocoder that operates at 48 kHz sampling frequency named WORLD vocoder. At the same four target bit rates, the sub-band Vector Quantized Variational AutoEncoder can reduce the Log Spectral Distortion around 0.93 dB in average.
Fractal Representation of Two-Dimensional Data Based on Wavelet Transform

An intermediate wavelet transform application for fractal data representation is considered. A description of the block wavelet transform was proposed. Mathematical expressions for different variants of such transformations are given. Using cluster analysis, the differences and advantages of the proposed approach are shown. The presence of invariance to a number of turns allows comparisons in the wavelet transform region necessary for the study of fractal data representation. In some cases, for wavelets with longer lengths, the recovery process diverged, but such bases are more promising for use.
INNOVATIVE APPROACH TO EDUCATION USING ICT SOLUTIONS – INFORMAL EDUCATION IN ELECTROMOBILITY

Appears in: ICERI2019 Proceedings Publication year: 2019Pages: 3147-3151ISBN: 978-84-09-14755-7ISSN: 2340-1095doi: 10.21125/iceri.2019.0801Conference name: 12th annual International Conference of Education, Research and InnovationDates: 11-13 November, 2019Location: Seville, Spain
Cognitive modeling of students' competencies development in Higher Education system

The article analyzes and summarizes the development of students' competencies. The authors use the cognitive modeling methodology of weakly structured systems to build cognitive maps of the educational process. The methodology contains the basic concepts of cognitive modeling using fuzzy cognitive maps using the impulse process and research on the impulse stability of the system. This methodology can be used to model any complex system, in particular the educational process of higher education. With the help of cognitive cards, a simulation of the development of professional IT competencies was carried out within the framework of the cognitive modeling methodology. Building cognitive cards to manage the competencies of IT professionals and imitation on their basis of managerial influences allow exploring the subject area.
Knowledge Representation and Logic Programming

This chapter shows that research in Logic Programming (LP), with its necessary extensions and improvements, can contribute a formal and efficient representation of knowledge that emerges from the recent research in Knowledge Representation (KR). It discusses some classical Artificial Intelligence (AI) paradigms and proposals to accommodate them into a logical framework. The chapter considers an important area of KR research, i.e. non-monotonic reasoning, which is producing a number of different non-standard logics to deal with common sense reasoning tasks, and is also playing a more and more important role in LP, especially for the treatment of negation. It reviews some of the more popular paradigms for representing knowledge which emerged from the AI community, namely production systems or rule based representations, associative representations such as semantic networks and object centred or frame based representations. The use of LP to solve KR problems is a very promising research direction and the cross-fertilization between the two fields can be very valuable.
Fuzzy Controller Structure to Solve a Problems of Local Extrema near the Reference Points

The paper refers to the second-order fuzzy controller structure, which allows to increase the accuracy of a fuzzy controller, to unify the synthesis and analysis algorithm, and to improve the efficiency of STC algorithm. The second-order fuzzy controller incorporates a fuzzy first-order controller and relies on the rule-based base with a double consequent.
Human Action Recognition Using Stereo Trajectories

This paper proposes a new method that uses a pair of uncalibrated stereo videos, without the need for three-dimensional reconstruction, for human action recognition (HAR). Two stereo views of the same scene, obtained from two different cameras, are used to create a set of two-dimensional trajectories. Then, we calculate disparities between them and fuse them with the trajectories, to obtain our disparity-augmented trajectories that is used in our HAR method. The obtained results have shown on average a 2.40% improvement, when using disparity-augmented trajectories, compared to using the classical 2D trajectory information only. Furthermore, we have also tested our method on the challenging Hollywood 3D dataset and, we have obtained competitive results, at a faster speed than some state of the art methods.
Forecasting Surabaya Rainfall in 2017 Using First Order Autoregressive Model through INLA Bayesian Approach

Abstract Water is one of the natural factors which affects the life of organisms on earth. If in one area, there is a sufficient amount of rain, then it will support the life of organisms in that area. However, if an area has an excessive amounts of rain, flooding will occur and it will damage the infrastructure, the agricultural land and some existing ecosystems. One way to reduce unwanted floods is by predicting accurate flood discharge. It can be used not only to design water buildings but also to manage water flow. Flood discharge can be predicted using the time series method, namely the First Order Autoregressive model, also known as the AR model (1). Estimating parameters in the AR model (1) can be done using the Moment, least Square and Maximum Likelihood methods. However, because the sample size used in this study is small then the Bayesian method can be used to estimate the AR model parameters (1). It has some advantages such as: 1. It can produce logical interpretations to conclude statistically in time series analysis 2. The output can always be updated based on the latest information. The Markov Chain Monte Carlo method is one method that can be used for Bayesian inference calculations, specifically the Gibbs sampler and Metropolis-Hastings algorithms. Both of these algorithms are more flexible and easily adapted to estimate complex models with many parameters or characterized by posterior nonstandard distributions. The MCMC theory states that the convergence distribution of the simulation value to the posterior distribution has a number of iterations to infinity, the posterior distribution will not be feasible. So that the processing of data consume a lot of time to reach convergence, then if it is not stopped then it will give suggestions about how some MCMC iterations become convergent. If the model is more complex then the MCMC algorithm is slower and the calculation becomes not feasible. Therefore, Rue et al. (2009) proposed a fast and accurate algorithm called the Integrated Nested Laplace Approximation Algorithm (INLA).
Study of Factors Related to Grin Cryptocurrency Mining Efficiency with GPUs

Grin cryptocurrency is one of the most recent implementations of Mimblewimble – specific stripped-down blockchain design as basis for strong privacy and good scalability features, which are complementing each other. Considering recent Grin inception and ongoing development there is a lack of research providing guidelines for optimizing mining efficiency in Grin’s network. In this study we aimed to experimentally test the influence of some factors on GPU mining efficiency, which should be taken into account. We have found, that choosing the right combination of mining software and GPU specific parameters are among them. In general, NVIDIA and AMD GPUs were comparably effective. The results may be relevant for creators of alternative cryptocurrencies, for which GPU mining is a part of design.
A Method for 3D-Metric Reconstruction Using Zoom Cameras

We propose in this work a practical method to compute the Euclidean (metric) 3D reconstruction of a scene, observed by a stereo pair of static, off-the-shelf, zooming cameras. The proposed method does not assume any form of explicit, pattern-based, calibration. The stereo system acquires a set of pairs of images, at different zooming levels, making it possible to obtain an affine calibration. The latter is obtained by taking advantage of the translation motion of the principal plane of each zooming camera. In particular, each pair of zoom images provides a pair of parallel planes that intersect at infinity. This makes it possible to estimate the principal point of each camera. Finally, a 3D metric reconstruction is calculated. Extensive experiments on both indoor and outdoor images have demonstrated the viability and accuracy of the proposed method.
M-Learning the Future of Learning, Analysis of its Usage Possibilities

Mobile learning or m-learning is the last stage of e-learning development. Todays milenium learners' cognitive styles, motivation, and skills in using mobile technology greatly influence the success and failures of usable mobile software solutions. This apparently affects their academic achievement. and what functionalities should an m-LMS support. The ecepctancy is that m-learning will no longer be a choice, some compulsive way of learning, in order to stay ahead of others. It does not fall under the category of "15 Minutes of Glory", but it is envisaged to become the dominant learning method for the growing mobile workforce, the new age. The increase in mobile device sales, the rapid growth in mobile web traffic, the growth of the adoption of mobile devices in the workplace, among other factors, have led to the development of the "mobile world" of m-learning. Therefore the research study has analysed all the most important factors influencing m-learning and issues and reccomendations are argumented and presented.
Seven Pleasures of Pris

The music in each of these tracks was created with artificial intelligence and machine learning. You will hear two AI-Bots: one in the centre uses soprano sax samples as its source, the other in wide stereo uses percussion. The two AI-Bots were programmed to respond to the other's sound and to contribute to the ongoing improvisation live and in realtime. Each AI-Bot is controlled by its own AI and is working without any human intervention. They are listening to each other and co-creating, and crucially doing something in the music that is beyond mimicry or behavioural response. The AI underpinning each Bot is driven by several Creative AI datasets and Machine Learning using a special process called embodied intelligence. The datasets are derived from real human musicians improvising with an AI-Bot. The AI operates on several concurrent processes: 1) raw data from the live music 2) dataset records of previous live improvisations 3) statistical correlations using multi-level perceptual neural-networks These are then controlled by an affect module that responds to the dynamics of the live improvisation and manipulates a gate system that recombines these streams into a final data flow. It is this that is used to drive the wheels of the physical bot and trigger the sounds.
Hybrid Scheme for Eye Center Localization in Color Images

Eye center localization is an essential step for the initialization of many face processing techniques like face recognition, facial expression recognition, face pose estimation methods and face tracking. This paper presents a novel technique to localize the eye centers by fusing the geometric and color information that related to the eyes region. The performance of the proposed method is evaluated on XM2VTS database. The validation shows that the eye detector has an overall 98.69% eye detection rate. In addition, experimental results demonstrate great accuracy in challenging cases (wearing glasses) and resilience to pose and illumination variations, achieving significant improvement over other existing methods.
Usability of QR code in the design of Information system for recognizing historic buildings, Kota Lama, Semarang

Abstract Urban infrastructure or basic facilities such as museum is essential as the component of smart city. To support a natural museum for instances the exhibit of historical building in “Kota Lama Semarang “or The old city of Semarang, this paper used the QR code to recognising the information on the historical buildings, Kota Lama, Semarang. Leaflet map of Semarang Historic building commonly used to provide the location information. However, leaflet map has a limitations, it cannot provide enough information about the historic building. The limitations of leaflet maps is only provide little information which explaining the condition of the historic building. To expand the information about the historical building, prior research suggested the use of web technologies. However, some people suggested the usage of leaflet – map which can show the location and the web site can provide more additional information about the historical building. In this paper, the researcher purpose a design of Information System, which employs Quick Response (QR) code technologies as a link to combine the information between leaflet map and web technologies. Then, the design validated with identify the usability of design for using QR code for recognising historic building, Kota Lama, Semarang. The method that used to evaluate the design is SUS (System Usability Scale). The QR code usability test using SUS question showed the number that the design is in level usable from the user perspective.
Online Management System of UPI FKIP YPTK Padang Education Field Practice

Abstract This study aims to develop the management system of PLK in the form of online system based on FKIP UPI YPTK Padang website that is valid, practical and effective. This is because there is no special system to accommodate PLK implementation process as PLK’s online management system. The type of research that the authors use is Research and Development research better known as R &amp; D. System test conducted on students at FKIP Prodi PTI UPI YPTK Padang. The test subjects consisted of the validity aspect of the system performed on 3 validators (expert), and the media practicality aspect that was done on 1 practitioner and 35 students who did the PLK. Instruments used in collecting data in the form of questionnaires of validity and practicality, and effectiveness. The data analysis techniques use Aiken’s V formula to find validity and calculate practicality percentages for practicality and use factor analysis techniques to search for the effectiveness of a website-based online management system. Based on the research that has been done, then obtained online management system based website PLK is www.fkipupiyptk.com, with validity value 0.80 Valid stated. While the average practicable result practiced by practitioners is 97.00% and is categorized as very practical, and the practical average by PLK students is 86.11% with very practical category. Effectiveness seen from the paired sample test t test, obtained a significance value of 0, 000 (0, 000 &lt;0, 05) means that there are significant differences in students who use manual systems with students who use the online system, thus the PLK online management system website is effective to use compared to the system manual.
Distributed Secure Storage System Based on Blockchain and TPA

With the rapid development of cloud computing technology, more and more users save a large amount of data in cloud storage. In addition to meeting the performance requirements, how to ensure the integrity of these data has become a hot topic for academic research in recent years. Provable data possession (PDP) based on trusted party auditor (TPA) is an important method to solve this problem. Decentralized storage based on blockchain technology, which has emerged in recent years, can well realize the proof of data possession. But it can’t seamlessly interface with high-performance cloud storage. In this paper, we propose a PDP model based on blockchain and TPA (BT-PDP). On this basis, a distributed secure file system (FS) is implemented to realize a BT-PDP proof of massive electronic data.
Methods of modeling objects using Petri nets

There are various elementary networks that are well suited for modeling simple objects and systems, as well as for representing some general patterns inherent in the most complex systems. All varieties of elementary Petri nets are modifications of a simple Petri net. This work is devoted to solving the problem of modeling critical systems based on the use of modified Petri nets. The dual (binary) Petri net is one of the modifications that allows you to simultaneously view inversion events, solving the problem with the possibility of dead ends. The construction of schemes using fuzzy logic allows you to calculate the values of linguistic variables of the acquired knowledge. The double Petri net allows you to organize the exclusion of negative events by introducing additional links. In accordance with the rules, it is possible to construct a double fuzzy Petri net, which involves the use of maximum and minimum transitions or the corresponding logical calculations of conjunctions and disjunctions. The transition from classical Petri nets to double fuzzy networks implements fuzzy knowledge of logical inference, which makes it possible to build expert systems with fuzzy logic that solve the problem of data analysis.