Reviewerly/exHarmony huggingface dataset:
Главный фактор эффективности деятельности организаций стoит инвестиций

The discovery made at the intersection of human sciences and the informatization of society is described, it can only be compared with the discovery of a periodic system of chemical elements. The necessity of educating personnel at all levels regarding it is shown. Socionics offers objective methods for finding the causes of contradictions in society, in production and other groups, in the family, and methods for eliminating these contradictions.
Effects of Internet Literacy on Cognitive Capabilities of Middle School Students

Internet services for education are technological facilities as basic needs to obtain information quickly and accurately, but not all literacy abilities of students are the same, so more identification is needed to reveal the impact of internet services for students.The purpose of this article is to explain the influence of internet services on the cognitive abilities of middle school students related to information literacy competencies.The method used is a quantitative method with data from secondary school students totaling 64 students analyzed using discriminant analysis, which reveals the causality of the variable internet service with information literacy competencies.The results show a significant influence of internet usage on certain variables on the cognitive abilities of middle school students, especially on information literacy abilities.The implication of this study is the disclosure of supporting variables from internet services in the world of education that support the 21st-century learning pattern characterized by promoting flexibility and efficiency.
Blockchain electronic vote system

One of the most critical applications in terms of data security and integrity is the electronic voting process, since it is a system that must be transparent and reliable, as well as safeguarding the identity of voters. This paper proposes a voting system based on Blockchain technology for data security, which allows verifying transactions in real time, ensuring high availability of the service without the need for a centralized and secure database thanks to its cryptographic keys or Hash and smart contracts. The Agile Scrum methodology is used for the development of the application, this allows to make unforeseen changes after each sprint, which allows obtaining optimal results in terms of software quality. The validation of the proposed voting system has been done by capturing the following data: gas consumption and time to complete the transaction; both in a local network and in an external network, always using a virtual private server (VPS).
BUG PREDICTION: Log approach – version approach

Bug prediction has generated widespread interest for a long time. The general scenario have been many applications with different approaches. The raising of properties of programming languages made it necessary a study about the correlation between classes, packages and files. In order to improve the quality of code and the developers satisfaction. In the last 20 years there are studied many metrics to evaluate a coding and to limit bugs. In further detail for instance, the Chidamber and Kemerer (CK) object-oriented metrics suite based on coupling between objects, numbers of children or depth of an inheritance tree. We will focus on different levels of granularity (class, method or package), paying attention on a featuring selection like to reduce or to combine metrics. In this work using the last Data analysis approach (neural network, decision tree, linear regression), it was possible to obtain models in order to predict bugs based on five relevant software system (Eclipse JDT Core - Eclipse PDE UI etc.). There models based on the purpose to have an exact prediction of numbers of bugs or to have the knowledge of a present / absence of bugs during the execution or programming. This is useful essentially for the developers to understand the relationship between bugs and software because the modern laugages programming we have a lot dependencies, just think about library, operative system and the several versions of programs. Using the CK metrics have prove that correlation between metrics is more reliable with some software system (eclipse and equinox). To obtain the same level of correlation with other software we need to combine in a specific approach the metrics (with also some interpolations). The hybrid metrics developed, correlated with the bug accurence return a level about 0.8 and 0.9 of correlation using the neural network and decision tree developed in this discussion. While the classification approach, (bug present or absence) developed for the first time with these programs, using the combinated metrics, the result will show very good values of precision, recall and accuration.
Rancangan Aplikasi Seleksi Atlet Taekwondo Menggunakan Framework Codeigniter Dengan Metode TOPSIS

Taekwondo is one of the sports in martial arts originating from Korea. Someone who wants to take part in a taekwondo competition usually has to take part in the selection held. The selection process in determining the selection of taekwondo athletes is still having problems. In the field there are still obstacles in the selection of athletes caused by systems that still use manual or conventional methods. Apart from that decision making cannot see the criteria in achievement together. The shortcomings in the athlete selection process are the existence of fraudulent selection of trained athletes, as well as the slow process of determining the assessment of selected athletes. To solve the problem, a decision support system is designed to increase the effectiveness of decision making and produce optimal decisions. In this decision support system the method that can be used is the TOPSIS method. Assessment criteria used as a reference for assessment are technique, tactics, mental, physical, age, reflexes and flexibility. The criteria will be a reference for obtaining the final score.
Evaluating the State of Mind of Sports Leaders of Children with Autism (Case of the Anatolian Area of Istanbul).

This research was designed to assess the state of mind of sports leaders of children with autism. Their moods were analyzed using age and gender variables. Also, suggestions were made at the end of the research based on the results of the evaluation.The population of the research comprised of sports leaders of children with autism; the sample of the research was 50 sports leaders (26 female, 24 male) of autistic children in the Anatolian area of Istanbul. The Symptoms Checklist-90 Revised (SCL-90-R) was used to determine the moods of the sports leaders. This scale was developed by Derogatis et al. (Derogatis, Lipman, Richels, 1974), and its validity and reliability studies were actualized by Kilic (Kilic, 2016) in Turkey.Regarding the analysis of data, frequency and percentage analyses were utilized to specify the descriptive characteristics of the sports leaders that participated in the study. T-test and Tukey test were used to review the differences in psychological symptom levels based on the descriptive characteristics of the sample group.There was no statistically significant difference in the gender variable of sports leaders of children with autism (p>0.05). As age increases, the levels of obsessive-compulsive disorder, interpersonal sensitivity, depression, anxiety, anger-hostility, phobic anxiety, paranoid thought, and General Severity Index (GSI) also increase. However, a significant difference was found solely in the anxiety sub-dimension (ANX) (p<0.05).An abstract is a brief, comprehensive summary of the contents of the article; it allows readers to survey the Keywords: Autism, Sports Leader, Psychological Symptoms, Sports
Study and implementation of an autonomous navigation algorithm for a scale electric car

This research describes the study of the autonomous navigation algorithm named Pure Pursuit. First, simulations were carried out in Matlab to evaluate its performance and then it was implemented in the embedded system myRIO of a scale electric vehicle called Aguara'i. It was possible to establish the values of lookahead distance so the navigation errors do not exceed a pre-defined threshold. For example, in a path for bicyclists at the city of Hernandarias for a velocity of 2.5 m/s the anticipated distance was about 1.8 m. One of the implementations developed was carried out in the Robocar Race 2018 competition (Santo Andre, Brazil), where the algorithm had a good performance, leaving Aguara'i with the 4th best time.
Fase-AL - Adaptation of Fast Adaptive Stacking of Ensembles for Supporting Active Learning

Classification algorithms to mine data stream have been extensively studied in recent years. However, a lot of these algorithms are designed for supervised learning which requires labeled instances. Nevertheless, the labeling of the data is costly and time-consuming. Because of this, alternative learning paradigms have been proposed to reduce the cost of the labeling process without significant loss of model performance. Active learning is one of these paradigms, whose main objective is to build classification models that request the lowest possible number of labeled examples achieving adequate levels of accuracy. Therefore, this work presents the FASE-AL algorithm which induces classification models with non-labeled instances using Active Learning. FASE-AL is based on the algorithm Fast Adaptive Stacking of Ensembles (FASE). FASE is an ensemble algorithm that detects and adapts the model when the input data stream has concept drift. FASE-AL was compared with four different strategies of active learning found in the literature. Real and synthetic databases were used in the experiments. The algorithm achieves promising results in terms of the percentage of correctly classified instances.
On the Layer Choice of the Image Style Transfer Using Convolutional Neural Networks

In this paper, the layer choices of the image style transfer method using the VGG-19 neural network are studied. The VGG-19 network is used to extract the feature maps which have their implicit meaning as a learning basis. If the layers for stylistic learning are not suitably chosen, the quality of style transferred image may not look good. After making experiments, it can be observed that the color information is concentrated on lower layers from conv1-1 to conv2-2, and texture information is concentrated on the middle layers from conv3-1 to conv4-4. As to the higher layers from conv5-1 to conv5-4, they seem to be able to depict image content well. Based on these observations, the methods of color transfer, texture transfer and style transfer are presented and make comparisons with conventional methods.
Impacto del uso de un Entorno Virtual de Aprendizaje en el Proceso Educativo como Alternativa a la Formación Presencial

Currently the use of information and communication technologies (ICT) are present in the vast majority of aspects of human life, one of them is education, which has undergone changes due to the use of these technologies and today it is possible learn at a distance, at any time and still have an evaluation and monitoring of the knowledge acquired. This article will show the results obtained by analyzing how much and at what level virtual education helps in the fields of competitiveness and productivity of students who have decided to opt for this system, through the search for different scientific articles that allow to create points of comparison in the strengths and weaknesses of virtual education. In addition, studies that are emphasized both in students 'and teachers' experience will be taken into account to create a more objective position about impact.
To Beep or not to Beep: On the Influence of some Interaction Design Variables onto Its Performance

During the construction and development of graphical interfaces, it is important to decide among a huge number of possible feedbacks (colors, sounds, etc.) with graphical variants (circular or rectangular shapes) and graphical behaviors (Close-and X-Button in title-bar e.g. to close a window).In this paper, the results of a long-term experiment comparing mouse-and touch-based interaction are presented.The aim of this work is to compare design variables of interaction in order to explore the influence of these variables on the interactions performance.The obtained results, for mouse interaction, reveal that only one studied design variable (clicking or not when reaching a target) is independent from target size.Color feedback showed to have negative influence for large objects and positive influence for small objects.For small targets circle-shaped targets and sound feedback proved to be negative, on the contrary to touch interaction.Here sound feedback saves for small objects 14.5% of interaction time.Finally the best results obtained are condensed to simple to apply design rules.
Blockchain: from Invention to Transformation

A massive population believes that the blockchain would be as extensive as Internet was, as blockchain provides transparent and secured transactions. Blockchain was introduced in 2008 with the invention of cryptocurrency, bitcoin. Bitcoin and blockchain are confused as same but they are not same, as blockchain offers more operations than bitcoin and is used for more than cryptocurrency. This technology has transformed digital world by bringing new outlook to adaptability, reliability and productivity of systems. Not only large companies want to adopt this technology but small companies are also interested in this transformation. It provides a tamper proof system to interchange any form of good, service or transaction and offers lower transaction costs with an entrust agreement supervised without arbitration from intermediaries who may not add direct efficacy. It promotes participation, accordance and smart contracts with implicit, resilient networked security attributes. This paper presents extensive succinct on blockchain technology and provides comparison of traditional vs blockchain transactions. Also the study focuses on, effective summary of blockchain, its components, technicalities, types, use cases in financial and non-financial sectors and how small companies can harness this advance technology and get benefit out of it. This paper focuses, not only on the benefits, future scope and the adoption of this technology in various sectors but the risks and limitations associated with it while incorporating it in the live environment.
Research on the multi-scale network crowd density estimation algorithm based on the attention mechanism

Whether it is daily urban traffic or some special gatherings, crowd gathering scenes are common, and it is becoming more and more important to calculate the number of people in terms of safety and planning. Calculating the number of people in high-density crowd is a very difficult challenge due to the diversity of ways people appear in crowded scenes. This paper proposes a multi-branch network structure that combines the dilated convolution and attention mechanism. By combining dilated convolution, the context information of different scales of the crowd image are extracted. The attention mechanism is introduced to make the network pay more attention to the position of the head of the crowd and suppress the background noise, so as to obtain a higher quality density map. Then add all the pixels in the density map to get the total number of people. Through a large number of experiments, this network can better provide effective crowd density estimation features and improve the dissimilarity of density map distribution, which has better robustness.
Analysis of chroma pixel value prediction using luma pixel values

In this paper, we propose a new mathematical method that can improve the accuracy of reconstruction luma to be able to choose the correct method of restoration for screen content images (SCIs). After receiving the decoded luma image and subsampled chroma image from the decoder, SSE (the sum of squares due to error) minimization is proposed to identify the used chroma subsampling scheme before compression. By using our method, subsampling reconstructed can be predicted more precisely through our way.
The CLASSLA-StanfordNLP model for lemmatisation of non-standard Croatian 1.1

The model for lemmatisation of non-standard Croatian was built with the CLASSLA-StanfordNLP tool (https://github.com/clarinsi/classla-stanfordnlp) by training on the hr500k training corpus (http://hdl.handle.net/11356/1183), the ReLDI-NormTagNER-hr corpus (http://hdl.handle.net/11356/1241), the RAPUT corpus (https://www.aclweb.org/anthology/L16-1513/) and the ReLDI-NormTagNER-sr corpus (http://hdl.handle.net/11356/1240), using the hrLex inflectional lexicon (http://hdl.handle.net/11356/1232). These corpora were additionally augmented for handling missing diacritics by repeating parts of the corpora with diacritics removed. The estimated F1 of the lemma annotations is ~97.54.The difference to the previous version of the lemmatizer is that now it relies solely on XPOS annotations, and not on a combination of UPOS, FEATS (lexicon lookup) and XPOS (lemma prediction) annotations.
Coalition of IoT and Blockchain: Rewards and Challenges

IoT and Blockchain are two evolving technologies which are gradually realizing immense potential to be a decisive part of future of mankind ecosystem. Blockchain and IoT, both are envisaged to bring in a plethora of advantages including better control, communication, transparency and more significantly realizing digital trust without any third party intervention. Both of these technologies have immense potential for exploitation in a smart nation concept. The advantages being realized are potent enough for definite implementation ahead but they come with an austere package of security concerns which if not taken care at the design stage can lead to pandemonium beyond control because of the billion plus connected things. Even at design stage, one can appreciate that it will be envisaging beyond control to close all security vulnerabilities and zero day’s exploits of future. But then Blockchain is an inexpugnable solution to shut all these securities imperils. This paper builds upon the advantages of the union of these two evolving technology behemoths, their union and solutions vide Blockchain to the challenges in the way ahead.
Cooperative Fish and Wildlife Research Units program—2019 year in review

First posted February 13, 2020 For additional information, contact: Cooperative Fish and Wildlife Research Units ProgramU.S. Geological Survey12201 Sunrise Valley DriveMail Stop 303Reston, VA 20192 Dear Cooperators:Members of the Cooperative Research Units are pleased to provide you with the “2019 Year in Review” report for the Cooperative Fish and Wildlife Research Units (CRUs). You will first note that this report looks a little different than those published in the past few years, as we opted for a shorter, more concise format this year. Inside you will find brief descriptions of just a few highlighted activities of unit scientists, students, and cooperators in support of our joint mission. Because of the shorter format, we are not able to include activities from every unit or State, but rest assured that we continue to value the great work that all of you do across the country and around the world.In fiscal year 2019, the CRU program was very productive despite challenging conditions, including budget uncertainty, a month-long furlough, and hiring delays. John Organ, Chief of the CRU program, retired in January 2019. The process to replace John was delayed several times, but as I write this, the position has been announced on the Federal Government recruitment site. I am hopeful that by the time you read this, we will have a new permanent chief. Congress provided an increase of $1 million in our allocation for the express purpose of filling some of the vacancies in our scientific workforce. Since receiving that increase, the management team has been working to fill vacancies.The program is fortunate to have excellent research scientists, dedicated leadership, and an outstanding administrative staff. However, our accomplishments depend on the tremendous support from all of you. We look forward to a productive 2020.John D. Thompson
Machine Learning Random Forest Cluster Analysis for Large Overfitting Data: using R Programming

This review article clearly discusses machine learning random forest clustering analysis for large over fitted data using R Programming which has been sufficiently explained with sampled data to summarized research analysis. Although it is difficult to create a random forest, it is a simple algorithm with various option with good indicator of the importance to its characteristics, there is large gap between data analysis and its design in research to address over fitted research data, Its main objective is to explain the simplest form of machine learning random forest cluster analysis whose data structure has been widely dispersed using software R whose results have been sufficiently explained to obtain intermediate results and graphical interpretation also to draw conclusions from large sets of research data. Therefore, this document presents the simplest form of random grouping of CTG data from internet and their strengths for data analysis are using R programming.
Acquisition and management of serials in selected academic libraries in Edo state of Nigeria

This study investigated acquisition and management of serials in academic libraries in Edo State of Nigeria. Four (4) research objectives were formulated for this study. These were to: determine how serial collections are acquired in the selected academic libraries in Edo State of Nigeria; investigate how serials are organized for easy retrieval in the selected academic libraries in Edo State of Nigeria; find out how serials are preserved in the selected academic libraries in Edo State of Nigeria; and solicit solutions for improving the management of serials in the selected academic libraries in Edo State of Nigeria. The study adopted a descriptive research design. The study targeted a total of 14 (fourteen) academic libraries in Edo State from which a sample of 173 respondents was generated using a total enumeration sampling technique. The study used a structured questionnaire; the copies were completed and returned by 57.8% of the respondents. Data collected were analyzed using frequency counts, percentages (%), mean (), and standard deviation (SD) to meet the study’s objectives. The study’s results have revealed that academic libraries in the study area acquire serials through various methods and use various means to organize them for easy retrieval. The libraries also use various methods to preserve their serials. Regarding improving serial management, the study findings have come up with a number of ways to do so. Based on the findings, the study recommends among others that academic curriculum should be enriched with serial skill acquisition and management contents; and academic libraries should consider acquiring more e-serials because it is very easy to manage and do not get damaged.