Reviewerly/exHarmony huggingface dataset:
Bayesian approaches for flexible and informative clustering of microbiome data

We propose two unsupervised clustering methods that are designed for human microbiome data. Existing clustering approaches do not fully address the challenges of microbiome data, which are typically structured as counts with a fixed sum constraint. In addition to accounting for this structure, we recognize that high-dimensional microbiome datasets often contain uninformative features, or noise operational taxonomic units (OTUs), that hinder successful clustering. To address this challenge, we select features which are useful in differentiating groups during the clustering process. By taking a Bayesian modeling approach, we are able to learn the number of clusters from the data, rather than fixing it upfront. We first describe a basic version of the model using Dirichlet multinomial distributions as mixture components which does not require any additional information on the OTUs. When phylogenetic or taxonomic information is available, however, we rely on Dirichlet tree multinomial distributions, which capture the tree-based topological structure of microbiome data. We test the performance of our methods through simulation, and illustrate their application first to gut microbiome data of children from different regions of the world, and then to a clinical study exploring differences in the microbiome between long and short term pancreatic cancer survivors. Our results demonstrate that the proposed methods have performance advantages over commonly used unsupervised clustering algorithms and the additional scientific benefit of identifying informative features.
Features of emotional, social intelligence and self-attitude of students of special defectological education

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AN EFFICIENT FRAMEWORK FOR COHESION AND QUALITY TOPICAL PHRASE MINING USING QBAALGORITHM

A phrase in a sentence represent a continuous word that represents some meaningand by identifying such phrases from large text documents corpus phrases we can helpresearchers to get required documents just by seeing those phrases. For example in givencomplete following sentence Support Vector Machine is a data mining algorithm to predict theclass of similar data. From this sentence, a continuous word like Support Vector Machine iscalled phrase and by seeing that phrase any researcher or normal person can understand thatdocument is describing the topic called Support Vector Machine. Usually, the technique oftopical word mining is twofold: word mining and subject matter modeling. For word mining,present processes frequently are afflicted by order touchy and irrelevant segmentation problems,which lead them to frequently, extract inferior first-rate phrases. For subject matter modeling,conventional subject matter fashions do now no longer absolutely do not forget the limitationsprecipitated with the aid of using phrases, which might also additionally weaken the cohesion. Inthis paper, we endorse an Efficient Framework for Cohesion and Quality Topical Phrase Miningthe usage of QBA Algorithm. A top notch word has to fulfill frequency, phrases, completeness,and appropriateness criteria.
Improving writing recount texts through semantic mapping

The research was conducted with the aim of to applying semantic mapping to improve students’ ability in writing recount texts of the second grade of SMPN 1 Metro Lampung.This was a classroom action research which was conducted in two cycles. Each cycle consisted four stages: planning, acting, observing, and reflecting. The research subjects were 25 students-nine boy students and sixteen girl students. The data were collected through observations, tests, and questionnaires. The research instruments consisted of observation sheet, tests, and questionnaires. The data from the observations and the learning achievement tests were analyzed using the quantitative technique. The success indicator in this study is that the students’ writing skill improves if, in terms of the learning mastery in the writing skill, of the students scored at least 80. This research shows that the use of semantic mapping improves the students’ writing ability in grade VIII.1 students of SMPN 1 Metro Lampung. The improvement is seen from the results of observation and students’ writing tests. The observation result shows that the students’ activeness in cycle I is middle and the students’ activeness in cycle II is high. Based on the results of students’ writing scores, the mean score of the pretest is 64,08, the mean score of the first cycle is 80.48, and the mean score in cycle 2 is 88.60. From those results, it can be concluded that semantic mapping strategy can improve the students’ writing in the recount texts.
Scherzo for Piano Trio

Author(s): McDaniel, Marshall | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
On Making Robots Proactive

The question addressed in this thesis is: Can we make robots proactive? Proactivity is understood as self-initiated, anticipatory action. This entails the ability to generate own goals and pursue t ...
Traditional Innovative and Technological Means of Assessing the Results of Knowledge

The problem of measuring and evaluating learning outcomes is one of the most important in pedagogical theory and practice. The solution of this problem is necessary for assessing the effectiveness of pedagogical innovations and technologies.The complexity of pedagogical phenomena, as well as the presence of a large number of factors, including random factors that affect the pedagogical process and its results, lead to the fact that the pedagogical process can not be regarded as completely deterministic. With the most perfect organization of the pedagogical process, we can`t unequivocally predict what the results of training will be for each individual student.In connection with this, the modern education system puts forward a demand: each teacher should strive to improve the objectivity of evaluation, use, along with traditional controls and innovative achievements in pedagogical science. The theme of hanging the effectiveness and quality of education and as a consequence of the pedagogical process represents an extensive field for study. This is due to the fact that with the development of human society, the development of all forms of activity.
HUMAN SECURITY IN MINING SYSTEM USING IOT

Over the past few years the transition of the Internet of Things (IoT) from research into its theory towards its practical application in our daily lives have been witnessed. It provides a mechanism for analysing both real-time data and past data, in which emerging artificial intelligence and data mining techniques play a key role. Although there is an increasing interest in applying the IoT in healthcare applications, there are still many challenges, such as finding ‘kits’ of IoT devices that could properly monitor a patient’s activity and track certain symptoms. Mining security means sensors information updates to web server using GPRS communication using TCP/IP and HTTP protocols. Now a day’s Many real time applications connected to web(internet).This is very use full and help full for customers to see application(requirements) from anywhere in the world. These web connected applications are belongs to server client relation. TCP, UDP and HTTP protocols are used in this concept. Data transfer to web server through GPRS (General packet radio services) communication. We can transfer long data through this GPRS.
DETECT AND PREVENT THE CREDIT CARD FRAUD TRANSACTION USING FACE RECOGNITION AND GRAY-LEVEL CO-OCCURRENCE MATRICESALGORITHM

In current days almost all users try to do online transactions by suing either credit /debit card or net banking, ratherthan by physical mode. As lot of users tries to perform the transactions online, intruders try to gain illegal profit bygaining the card details through some ethical techniques. In this modern world there is a huge need to provide moresecurity for the credit card transactions by using face recognition techniques and the same need to be included incredit card transactions. The transactions which were done on a physical medium changed tobe persisted internet, and thus with change in time and technology. In a recent analysis almost 85 percent oftransactions all around the world are literally being held online hence the trend of online transaction cameboth thanks to simple use also as increased security. Now this term is employed altogether most every transactionarea ranging from ordering things ranging through internet. In this present thesis in order to avoid the forgery ofcredit and debit cards, we try to link a new solution for the credit cards like biometric linkage between the signedfacial image of the credit card holder embedded in mastercard and therefore the user‟s facial image captured by awebcam during usage of the cardboard. The main goal of this proposed thesis is to match the similarity of facesembedded in the database and user by integrating the master card transaction with the face comparison. If thepictures are same then we will perform the transaction alternatively the authentication are going to be invalid.
Transfer Learning via &#120001; 1 Regularization.

Machine learning algorithms typically require abundant data under a stationary environment. However, environments are nonstationary in many real-world applications. Critical issues lie in how to effectively adapt models under an ever-changing environment. We propose a method for transferring knowledge from a source domain to a target domain via $\ell_1$ regularization. We incorporate $\ell_1$ regularization of differences between source parameters and target parameters, in addition to an ordinary $\ell_1$ regularization. Hence, our method yields sparsity for both the estimates themselves and changes of the estimates. The proposed method has a tight estimation error bound under a stationary environment, and the estimate remains unchanged from the source estimate under small residuals. Moreover, the estimate is consistent with the underlying function, even when the source estimate is mistaken due to nonstationarity. Empirical results demonstrate that the proposed method effectively balances stability and plasticity.
Generalized Do-Calculus Without Graphs

Inferring the potential consequences of an unobserved event is a fundamental scientific question. To this end, Pearl's celebrated do-calculus provides a set of inference rules to derive an interventional probability from an observational probability. In this framework, the primitive causal relations are encoded on a Directed Acyclic Graph (DAG), which can be limitative for some applications. In this paper, we capture causality without reference to a graph and we extend the rules of do-calculus to systems that do not possess a fixed causal ordering. For this purpose, we introduce a new framework which relies on the theory developed by Witsenhausen for multi-agent stochastic control. The mapping from graphs to so called Witsenhausen's intrinsic model is natural: the primitives of the problem are the agents' information fields; the random variables are synthesized by the agents whose strategies encode the informational constraints. All in all, our framework offers a richer language than DAGs and provides a generalized do-calculus.
High Dimensional Event Exploration Over Multiple Simulations

We introduce a visualization technique to analyze event simulation data. In particular, we allow the user to discover families of events based on the topological evolution of discrete events across simulations. Discovering how events behave across simulations has applications in financial market analysis, military simulations, physical mechanics, and other settings. Our approach is to use established methods to produce a linearized tour through the parameter space of arbitrary dimension and visualize events of interest in two dimensions. The first dimension is the tour ordering and the second dimension is usually time. This paper presents our novel approach and gives examples in the context of simulations of magnet dynamics. Our initial findings are that, while z-ordering does allow the user to analyze event families, other ordering techniques would likely improve the visualization by improving spatial locality.
The Effects of Self-Leadership on Problem Solving Ability and Career Preparation Behavior : Focusing on the mediation effects of Problem Solving Ability in the case of Airline Service Department’s Students

It is essential for Airline Service Department to educate students and give a guide line to its students enough to develop their own career in the airline service field. Recognizing the importance of Self-Leadership, Problem Solving Ability in order to enforce Career Preparation Behavior of students, this study planes to examine the relationship among Self-leadership, Problem Solving Ability, and Career Preparation Behavior. For the sake of enhancing Career Preparation Behavior, this study undertook a theoretical approach followed by a statistical analysis. The self-Communication method was adopted to collect the data during January in 2020. The valid survey of 320 students majoring in Airline Service was selected and analyzed by SPSS 20.0 and AMOS 20.0 program. The results of findings were as follows: First, both Behavior-focused strategies and Constructive thought pattern strategies of Self-leadership shows significant effects on Problem Solving Ability. Secondly, only Natural reward strategies of Self-Leadership shows a significant effects on Career Preparation Behavior. Thirdly, Problem Solving Ability doesn't show any direct effects on Career Preparation Behavior. However, Problem Solving Ability plays mediation effects between Self-Leadership and Career Preparation Behavior. It is required to adapt appropriate tools such as their self-leadership program, problem solving activities and consulting activities in order to enhance Career Preparation Behavior.
A Comparative Analysis of Different Approaches for Recognizing Human Activity

This research paper is based on study of existing methods for identification and analyzing the human activities. Many scholars have done their work with respect to the understanding of human behavior. Literature survey and comparative examination of identification of human behavior provide a schematic review of the various methods available for choosing the correct approach under a given situation Data Mining can be employed for extracting knowledge for recognizing human activity effectively.
Preludio para piano Op.1

Author(s): Junchaya, Rafael Leonardo | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
Malaria Detection using Convolution Neural Network

Malaria a disease which is infected from the bites of mosquitoes which are transmitted to the people caused by the parasites. The qualified technicians examination the microscopic blood smears for the parasite-infected red blood cells from the standard diagnosing method for malaria. The person who is doing the examination have to know the diagnosis method which is inefficient and the malaria which depends on the knowledge and experience. Using deep convolution neural network we have some of our recent research on highly accurate information of malaria which is infected the blood cells. The deep learning methods which have the advantage of being able to learn the features from the input data given. The CNN process is used with more accurate in determining the results and reduces the computation time. The cells of the microscopic images which are used for identifying  the presence of malaria-infected parasites using image processing techniques, type of parasite and their stages of the malaria misdiagnosis can be considerably minimize the number deaths occurred.How to cite this article:Hanitha G, RajyaLakshmi A, Hemasree B et al. Malaria Detection using Convolution Neural Network J Adv Res Appl Arti Intel Neural Netw 2020; 4(1): 27-32.
Agent-based Modeling and Simulation for Evacuation of Landslides Natural Disaster

Landslides are natural disasters that pose a threat which is quite high in the area of Batu, East Java, Indonesia. The occurrence of landslides has a negative impact on environmental damage and even fatalities. These impacts can arise due to a lack of planning in disaster management preparedness. Therefore better planning is needed to minimize the negative impacts that arise. Improvement of planning can be done by conducting evacuation simulations. However, the existing evacuation simulation is still static with one scenario that is done repeatedly. Therefore, a more dynamic evacuation simulation is needed to represent the various parties involved in it and to apply various scenarios. Such dynamic simulations can be facilitated using agent technology. Agents can describe autonomous behaviour and can communicate in their environment to achieve a goal. Apply the capabilities of these agents by modelling and simulating the evacuation process can provide an illustration for a more dynamic process of landslide evacuation. This research presents an agent-based landslide evacuation model and the simulation results from this model. The results are concerned that, by using agent technology can apply simulations with various conditions. So with these results can be used as a reference in the handling of natural disasters that occur landslides.
APPLICATION OF R STUDIO TOOLS FOR ANALYSIS OF FACTORS AFFECTING ENERGY CONSUMPTION

Reducing energy consumption is one of the priority areas of development for all energy consumers. The choice of an efficient and reliable programming language will provide a qualitative analysis of all possible impacts, and consequently a more rational energy consumption by consumers and improve the quality of energy management. The main purpose of this work is to determine the means of R Studio to identify the most influential factors in energy consumption. Information technology allows you to process large databases, as well as use mathematical tools to identify factors that affect the level of energy consumption. R Studio is an open source integrated shell and has a user-friendly interface that simplifies working with R. A number of features, such as backlighting and auto-completion, easy script navigation and others, make R Studio attractive for analyzing statistical databases with many variables. This article describes in detail the contents of the main R Studio window and its main functionality. On the example of the enterprise database the mathematical tools of R Studio were considered: the matrix of pair correlation coefficients for factor signs is constructed, the correlation analysis of influence of factors on energy consumption is carried out.
Software Process Improvement Implementation Issues in Small and Medium Enterprises That Develop Healthcare Applications

Software Process Improvement (SPI) intends to recuperate software processes to realize high quality software. But numerous SPI initiatives predominantly in the case of software Small and Medium Enterprises (SMEs) are failed to achieve desired results as certain issues occur during this progression. Objective of this research work is to facilitate the efficacious SPI implementation in the case of software SMEs that develop healthcare applications. The study identifies and ranks common SPI implementation issues in the case of related SMEs. For this purpose, two questionnaire surveys have been performed by involving relevant software industry practitioners. In the first survey, by providing a literature-based list of SPI issues, we have solicited respondents to choose common issues or resistant factors for SPI in the case of SMEs that deal with healthcare application development. We have also requested the practitioners to mention the issues that they have been generally spotting during the SPI in case of pertinent SMEs but have not been mentioned in the given list. During the second survey, by employing two rounds of the Delphi method, practitioners have ranked the commonly transpiring SPI issues regarding SMEs that deal with the development of healthcare applications. The ranking is based on the issues' impact having four categories: catastrophic, serious, tolerable and insignificant. To incorporate various SMEs standards that are followed worldwide, the concept of 'common/shared range standard' is presented. The study identifies 26 SPI issues in the case of SMEs that develop healthcare applications whereas top 10 issues instigate from finance and management. To enable swift and fruitful SPI in the case of pertinent SMEs, this study suggests that the 26 identified issues must be tackled proactively whereas financial and managerial issues must be given top priority.
METHOD OF AUTOMATED GENERATION OF INFORMATION ABOUT UNIVERSITY’S SCIENTIFIC PUBLICATIONS FOR REPORTING IN THE RESEARCH MANAGEMENT SYSTEM OF THE RUSSIAN MINISTRY OF SCIENCE AND HIGHER EDUCATION

Manual preparation and uploading information on university’s scientific publications to the Research Management System takes considerable time, and often it is not able to meet the deadlines. This challenge posed the task of automating these processes to the authors of the study. The method involves the use of standard office tools (Microsoft Word and Excel), so that employees who do not have specialized information technology knowledge and have an average level of computer skills could use it. The study demonstrated a 3.5-fold time costs reduction when generating information about university’s scientific publications automatically as compared to manual data entry in the Research Management System.
NEW WAYS OF WORKING IN TIMES OF CRISIS IN HIGHER EDUCATION

Appears in: EDULEARN20 Proceedings Publication year: 2020Pages: 6388-6396ISBN: 978-84-09-17979-4ISSN: 2340-1117doi: 10.21125/edulearn.2020.1681Conference name: 12th International Conference on Education and New Learning TechnologiesDates: 6-7 July, 2020Location: Online Conference
THE IMPLEMENTATION OF SUMMARIZING ACTIVITY BY USING SOMEBODY WANTED BUT SO (SWBS) STRATEGY TO IMPROVE STUDENTS’ READING COMPREHENSION (AN EXPERIMENTAL STUDY TO EIGHT GRADE STUDENTS AT MTSN MODEL BANDA ACEH)

Abstract Name : Mursyida Students No : 1706202020018 Study Program: Master Degree in English Education Department : English education Tittle : The Implementation of Summarizing Activity by Using Somebody Wanted But So (SWBS) Strategy to Improve Students‟ Reading Comprehension (An Experimental Study to Eight Grade Students at MTsN Model Banda Aceh) Key Words:Reading Comprehension, Summarizing Activity; Using SWBS Strategy The aim of this research is to find out the significant difference between thestudents who are taught through summarizing activity using SWBSstrategy than those who are not taught through the strategy in terms of finding out main idea, specific information, word meaning, reference, and inference and to know the students’ responses toward the implementation of this strategy in reading classroom. This study employed true experimental design. There were two classes as a sample classified into experimental and control classes. The class was chosen by using cluster random sampling and each class consisted of 36 students. In collecting the data, test and questionnaire were used and the data were analyzed by using SPSS 21. The result of the study in the post-test found that the mean score at the experimental class is 84.78, and the mean score at the control class is 73.33. Meanwhile, the result of z-score between both experimental and control classes is 6.05 at the level significance of 5% (0.05). It indicates that there is a significant difference between the students who are taught through this strategy than those who are not taught through this strategy.Furthermore, the result of questionnaire showed that most students give the positive response toward the implementation of this strategy in the reading classroom. It got the better improvement toward their self-confidence, social interaction and also individual accountability.