Reviewerly/exHarmony huggingface dataset:
Most preferable combination of explicit drift detection approaches with different classifiers for mining concept drifting data streams

Sensors in the real-world applications are the major sources of big data streams with varying underlying data distribution. Continuously generated time varying data streams are commonly referred as concept drifting data streams. Many concept drifting data mining algorithms explicitly utilise the drift detection algorithms for ensuring the forgetting of out-dated concepts and learn new concepts upon occurrence of drifts. In concept drifting data streams, the accuracy of the learner depends on the accuracy of the drift detection algorithm and its promptness towards drifts detection. For maintaining the consistent high accuracy in the classification of concept drifting data streams, it is very important to understand the preferable combinations of drift detection algorithms with the classification algorithms. In order to explore such preferable combinations, this work presents an empirical evaluation of some popular drift detection methods with some state-of-art classification algorithms on some standard benchmark datasets of real world.
Towards Modeling Geographical Processes with Generative Adversarial Networks (GANs) (Short Paper).

Recently, Generative Adversarial Networks (GANs) have demonstrated great potential for a range of Machine Learning tasks, including synthetic video generation, but have so far not been applied to the domain of modeling geographical processes. In this study, we align these two problems and - motivated by the potential advantages of GANs compared to traditional geosimulation methods - test the capability of GANs to learn a set of underlying rules which determine a geographical process. For this purpose, we turn to Conway's well-known Game of Life (GoL) as a source for spatio-temporal training data, and further argue for its (and simple variants of it) usefulness as a potential standard training data set for benchmarking generative geographical process models.
Use Cases and Applications of Blockchain Technology in IT Industry

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Pengaruh Discovery Learning terhadap Kesadaran Metakognisi dan Hasil Belajar Peserta Didik

This study was conducted to find out the effect of discovery learning on student’s metacognitive awareness and cognitive learning achievement. The population of this research was all of the 11th grade MS (Mathematics and Science Program) students of Sumberejo 1 Senior High School. The research sample were students of 11th MS-1 and MS-3 class taken by cluster random sampling technique. This study was quasi-experimental with Pretest Post-test Non-Equivalent Control Group Design. In this study, student’s metacognitive awareness was measured by using MAI (Metacognitive Awareness Inventory) and SEMLI-S (Self-Efficacy and Metacognition Learning Inventory—Science). Meanwhile, student’s cognitive learning achievement was measured by using cognitive test. The data were analyzed statistically by independent sample t-test respectively at 5% significance level. The results showed that the discovery learning model significantly influenced student’s metacognitive awareness and cognitive learning achievement with significant value of each were 0,000. Through this research, we found that the discovery learning model significantly influenced student’s metacognitive awareness and cognitive learning achievement rather than discussion method.
Some cyclic codes of length ${8p^n}$ over $GF(q)$, where order of $q$ modulo $8p^n$ is $\frac{\phi{(p^n)}}{2}$

Let $G$ be a finite group and $F$ be finite field of prime power order $q$ (of type $8k+5$) and order of $q$ modulo $8p^n$ is $\frac{\phi(p^n)}{2}$. If $p$ is prime of type $4k+1$, then the semi-simple ring $R_{8p^n}\equiv \frac{GF(q)[x]}{}$ has $16n+6$ primitive idempotents and for $p$ of type $4k+3$, then $R_{8p^n}$ has $12n+6$ primitive idempotents. The explicit expression for these idempotents are obtained, the generating polynomials and minimum distance bounds for cyclic codes are also completely described.
Planning for the Implementation of the Electronical Neighborhood Unit Application

Along with developments, times, digital technology is growing and all activities will be carried out online because it is considered more practical and fast, and saves time. A neighborhood association is a community organization consisting of several residents and heads of households who have family cards (KK) that are domiciled in the neighborhood (RT) in one environment. Activities in the neighborhood include taking care of the boarding house domicile (stay report), making an electronic letter of identity card to the neighborhood residents (RW), making a domicile letter and providing information to residents, making a death certificate, moving a house. Sometimes the activities in the neighborhood also require quite a long time and the process is less efficient. For this purpose, an e-government-based website was designed for the neighborhood of the neighborhood called the electronic neighborhood association (RT). Neighborhood association electronics (E-Rt) is a website that is intended for residents in the community, namely to access activities in neighborhood neighborhoods. Making E-RT using Php Mysql and using the waterfall methodology
Clustering of Human Hand on Depth Image using DBSCAN Method

In recent years, depth images are popular research in imageprocessing, especially in clustering field. The depth image can captureby depth cameras such as Kinect, Intel Real Sense, Leap Motion, and etc.Many objects and methods can be implemented in clustering field andissues. One of popular object is human hand since has many functionsand important parts of human body for daily routines. Besides, theclustering method has been developed for any goal and even combinewith another method. One of clustering method is Density-Based SpatialClustering of Applications with Noise (DBSCAN) which automaticclustering method consists of minimum points and epsilon. Define theepsilon in DBSCAN is important thing since the result depends on those.We want to look for the best epsilon for clustering human hand in thedepth images. We selected the epsilon from 5 until 100 for getting thebest clustering results. Moreover, those epsilons will be testing in threedistance to get accurate results.
Alpha oscillations mark the interaction between language processing and cognitive control operations during sentence reading

The Eleventh Annual Society for the Neurobiology of Language Meeting (SNL 2019) (Helsinki, Finland, August 20-22, 2019)
Pitching Your Book to a Small Press

Women in Higher EducationVolume 28, Issue 10 p. 6-15 Publishing Pitching Your Book to a Small Press Katie Rose Guest Pryal, Search for more papers by this author Katie Rose Guest Pryal, Search for more papers by this author First published: 29 September 2019 https://doi.org/10.1002/whe.20763Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume28, Issue10October 2019Pages 6-15 RelatedInformation
Collaboration of Clustering Technique and Picture in Teaching Vocabulary

This research was aimed to know the empirical evidence about the improvement of the studentsâ€™ English vocabulary through Clustering technique and picture as a media at the First Grade Students of Madrasah Muâ€™alliminn Muâ€™allimat Bahrul â€˜Ulum Tambakberas Jombang. The problem of the study was how to improve studentâ€™s English vocabulary through Clustering Technique and Picture as a media. This pre-experimental research is quantitative and the data taken from the pre-test and post-test and test sheet is used as the instrumentation. The result showed that the use of clustering technique and picture as a media in teaching vocabulary mastery increased. It can be seen from the studentsâ€™ score of pre-test is 46.73, meanwhile the mean score of post-test is 73.67. The effectiveness of using this technique and media is implemented from studentsâ€™ scores which are increased after learning vocabulary by using collaboration between clustering technique and picture as a media.
Interdisciplinary Integration As A Way To Update Modern Education Content

The article presents modern approaches to the concept of “interdisciplinary integration” in the national and foreign pedagogy, in accordance with which the conceptual series of research is built. The experience of interdisciplinary integration using in the national school is given, its positive and negative sides are revealed. The issues of implementation of interdisciplinary integration in the comprehensive school and in higher educational institutions (high school) that are relevant for modern practice are noted. The authors indicate influence of the newest information technologies, the didactic possibilities of digital educational resources on interdisciplinary interaction. The novelty of the study lies in the fact that interdisciplinary integration is considered in conjunction with school - university (college). The results of the survey of university professors and school teachers are given, which allow teachers to understand the essence of interdisciplinary integration, as well as its level of dissemination in school practice, goals and methods of the interdisciplinary integration using. The survey was attended by teachers from several regions, urban and rural schools. Negative aspects of this process at school level are the following: precision differentiation in integration by cycles (social and humanitarian disciplines, natural- science); lack of integration of different kinds of activity; transfer activity methods from subject to subject; absence of tasks for real-life situations involving the synthesis of knowledge and skills from school practice and social experience of schoolchildren. The study showed that the actualization of educational content through interdisciplinary integration is associated with innovative forms and methods of integration.
Studies in Semantic Modeling of Real-World Objects using Perceptual Anchoring

Autonomous agents, situated in real-world scenarios, need to maintain consonance between the perceived world (through sensory capabilities) and their internal representation of the world in the for ...
VitaBoot: footwear with dynamic graphical patterning.

VitaBoot is a footwear concept incorporating dynamic graphical patterns which indicate the wearer's activity level. Whilst shoes are an important element in fashion wear and a lot of research has focused on shoes as input devices, comparable few concepts have explored the potential for their use as an output space. We created a boot design that incorporates dynamic patterning through the use of electrochromic (EC) displays embedded in the surface material. The boot was designed and constructed from scratch, using a faux leather material, ensuring the overall aesthetic of the design, including the integration of the required control electronics and power source. The boot connects wirelessly to a chest-worn heart rate belt, and pattern changes indicate when the wearer's heart rate is above a predefined threshold. VitaBoot demonstrates the potential for dynamic shoe patterning for aesthetic or functional means, and the suitability of flexible, low-power EC display technology in this domain.
Marathi Spoken Word Recognition using Spectral Domain Features over Distributed Frequency Content

Word recognition is one of the important area in speech recognition. Local language spoken word recognition is the next step in the technological advancement. This paper presents the new approach for Marathi word recognition using Spectral Domain features like Mel-frequency cepstral coefficients (MFCC) and spectral centroid over distributed frequency content. A very little or no work is done in Marathi spoken word recognition. That is the reason why no standard Marathi word recognition tool was available online. A dataset of 40 native speakers from different region including 20 males and 20 females is developed for total 20 words related to grocery items. The selected words are uttered in Marathi language. Each speaker uttered a word 10 times. The creation of the dataset for the Marathi words was the main contribution of this work. To the best author knowledge, the SVM classifier is used for the first time to recognizeMarathi words.Out of 40 speakers, 30 speakers feature set was used for training purposes and remaining of the 10 speakers feature set are used for testing.The results obtained from the purposed method are satisfactory and achieved 94.75 % overall accuracy.
Learning a smooth kernel regularizer for convolutional neural networks

Modern deep neural networks require a tremendous amount of data to train, often needing hundreds or thousands of labeled examples to learn an effective representation. For these networks to work with less data, more structure must be built into their architectures or learned from previous experience. The learned weights of convolutional neural networks (CNNs) trained on large datasets for object recognition contain a substantial amount of structure. These representations have parallels to simple cells in the primary visual cortex, where receptive fields are smooth and contain many regularities. Incorporating smoothness constraints over the kernel weights of modern CNN architectures is a promising way to improve their sample complexity. We propose a smooth kernel regularizer that encourages spatial correlations in convolution kernel weights. The correlation parameters of this regularizer are learned from previous experience, yielding a method with a hierarchical Bayesian interpretation. We show that our correlated regularizer can help constrain models for visual recognition, improving over an L2 regularization baseline.
Information system "Electronic University": the experience of Khmelnytskyi National University

The article is devoted to the development of a university management information system based on the experience of developing and implementing the Electronic University system at the Khmelnytskyi National University.We consider the main tasks solved by the university management system, taken architectural decisions, the principles of an effective database structure design, development tools, report generation, programming languages and frameworks.A comparative analysis of possible approaches is carried out and recommendations are made taking into account practical experience in using the system, which has been developed and used since 2001.The main business processes and functional structure of the information system are considered.The need and possibility of storing data that reflect the history of all changes are justified.This provides the possibility of obtaining a data slice or the state of a certain information object at any time by certain calculations in the database.It also gives you the opportunity to get almost any statistics for any interval or at any time.
M. ED. STUDENTS’ COMBINATORIAL INCLINATIONS ON PEDA-ANDRAGOGICAL ORIENTATIONS

Pedagogy is the art and science of teaching children. The basic content of pedagogy deals with knowledge, practice and belief or professional ethics of teaching. In the pedagogical orientations, the teacher has full responsibility for making decision about what will be learned, how it will be learned, when it will be learned. It is based on the assumption that learners need to know only what teacher teaches them. In pedagogical approach, learning experiences are more teacher-directed. It includes lectures, transmitting factual information, assigned readings, drills, tests and rote learning. Andragogy is the art and science of teaching adults. In other words, it is science and art of helping adults learn. The adult learner goes from being dependent to self-directed. The growth and development of andragogy as an alternative model of instruction has helped to remedy this situation and improve the teaching adults. In andragogical approach, learners are expected to be independent in learning and society acknowledges what people want to learn. In andragogical orientations, the role of teacher is that of a facilitator and it includes self-direction, autonomy, accountability and responsibility for decisions resource of experience, performance of social roles and immediacy of application or action. The peda-andragogical orientations are useful to refine the teacher and learner behavior in teaching learning process.
ENRICHING ENGLISH VOCABULARIES USING MOVIE SCRIPT IN READING CLASS

The purpose of this study is to get more in-depth implementation of movie scripts to increase vocabulary in reading classes. Vocabulary has a important role in understanding the contents of the reading text. The research method uses action research. So that, data analysis techniques use qualitative and quantitative data analysis techniques. The sample is taken as many as 25 students. The process of collecting data uses tests, observations, and interviews. The results showed that the vocabulary of students before and after using movie scripts was different. The average score of the student vocabulary test in the reading class showed a significant difference. The average of pre-test result is 56.2 and the post-test is 81.87
An Experiment on Automated Requirements Mapping Using Deep Learning Methods

Requirements engineering is one of critical activities in systems development for Automotive Industry. Its outcome is most often represented by a set of documents capturing requirements specifications in natural language. For quality assurance and maturity support of the final products, the requirements must be verified and validated at different testing levels. To achieve this, the requirements are manually labelled to indicate the corresponding testing level. The number of requirements can vary from few hundreds in smaller projects to several thousands in larger projects. Their manual labeling is time consuming and error-prone, thus sometimes incurring an unacceptable high cost. In this paper we report our initial results on the automated classification of requirements in two classes: “Integration Test” and “Software Test” using Machine Learning approaches. Our solution could help the requirements engineers by speeding up the classification of requirements and thus reducing the time to market of final products.
Touch screen haptic disconnection

Can we survive 24 hours without touch screen technology? Have you observed how we travel in the Underground? It is unbelievable how these devices have radically changed social dynamics in a decade. If our first primitive approach to aesthetics was through tactility, how is screen caressing affecting us? In an individualistic and image consumerist society, touch screens empower illusion and the spectacle. This exploratory research done, between 2016 and 2018, attempts to understand how touch screen might, paradoxically, detach us from our tactile and haptic instincts. This article concludes with prospective inquiries seeking to find an equilibrium in approaching new technologies without losing our humanity.
Comparison Method of Long-term Daily Life Considering the Manner of Spending a Day

Recently, a large amount of physical activity data has been obtained via wearable sensors collected as lifelogs. The long-term daily lives of users can be understood using such long-term activity data. In this paper, we investigate a method for comparing two distinct periods of the daily life of a user to understand the long-term characteristics of that user’s daily life. Our method uses only activity data that can be collected easily and continuously over the long term using wearable sensors. There are various ways in which humans can spend a day, and a period of daily life consists of a set of several days spent in several manners. We compare two periods of daily life by considering the manner in which a day is spent. The manner in which a day is spent can be distinguished based on the activities that are performed on a given day. The amount of movement differs depending on the activity, and similar amounts of movement are measured when similar activities are performed. We focus on this point to classify how each day is spent. Further, we distinguish the manner in which a day is spent based on similarities in the time series data with respect to the levels of the activities by noting the main sleeping period, which is an important behavior in daily human life. We propose a method to compare two distinct periods of daily life based on the distribution of the manner in which a day is spent in each period. The effectiveness of the methods proposed in this paper is evaluated via experimental evaluations using real datasets.
The Mediating Role of Institutional Factor on the Relationship between Entrepreneurship and Economic Growth

Entrepreneurship has long been perceived as a crucial determinant for economic growth. There has been a considerable upsurge in researches trying to determine the main elements driving entrepreneurship and the channel through which entrepreneurship generates economic growth; however, a global consensus has not been reached yet on theoretical, methodological and empirical levels.  The basic problem arises from the choice of appropriate variables reflecting the measures of the entrepreneurial activity and institutional environment and the outcome of such measures. This study examines the relationship between entrepreneurship and economic growth as well as the determinants of entrepreneurship in an unbalanced data set for 86 countries for the period 1996-2015 by considering different measures of entrepreneurial activity (TEA and Business Density) and different institutional arrangements (Distance to Frontier, Global Competitiveness index and composite governance index). A system of simultaneous equations is adopted in order to adjust for the fact that we are not able of controlling all possible bases of endogeneity between Entrepreneurship and institutions.  Results have revealed different coefficients sign and magnitude based on the measures being assessed.  Our findings suggest that institutional variables have positive and significant effect on entrepreneurship measured by Business Density and the latter has also a positive effect on economic growth though the significance level differ depending on the institutional variables employed. Similar conclusions cannot be drawn for entrepreneurship measured as TEA where certain measures of institutions appeared to have e negative effect on entrepreneurship and the latter has also a negative effect on economic growth.