Reviewerly/exHarmony huggingface dataset:
Improved Tweets Polarity Detection using Lexicon-based Features and Caching

Tweet Polarity detection the process of observing and identifying the sentiment inclination of text, whether it is positive or negative. In this paper, improved polarity detection on tweets using supervised learning is proposed. This method is using data sets available in public. The pre-processing is improved using proper caching of data items to save the time for processing of duplicate items in data sets. The feature selection strategy ensures reduced dimensionality. The low dimension data improves the classification efficiency. The experiment shows that the method is improving the overall performance in training and testing of polarity detection.
Development of Novel Average Neuro Fuzzy Hybrid Control Technique for Robot Navigation in Unknown Environments

The current research focuses on development and analysis of novel Average Neuro-Fuzzy Controller for path planning and navigation of mobile robot in highly cluttered environment. During the investigation various researches related to robot, control and navigation have been analysed. For mapping the environments several distance sensors mounted on the robot are used. The sensors readings about the environments have been segmented into various sectors (front, left, right and back sectors). Using the sensors reading robots negotiate with the obstacles present in the environments during navigation from start to goal point. Experimental and simulation results obtained during the current research from various exercises are in agreement and are within 3%. Comparisons between results show the effectiveness of the proposed technique for robot navigation in complex environments. This technique can be used to address various engineering optimisation problems.
BRAIN NATRIURETIC PEPTIDE (BNP) SEBAGAI BIOMARKER GAGAL JANTUNG KONGESTIF

Brain Natriuretic Peptide (BNP) is mainly secreted by the heart ventricles and acts as an antagonist to Renin-Angiotensin-Aldosterone. BNP is secreted as pre-proBNP which is broken down into BNP and proBNP in circulation. The BNP examination is done by measuring the levels of BNP or N-Terminal-proBNP depending on the method and the manufacturer. Increased levels of BNP and NT-proBNP indicate heart failure so that BNP and NT-proBNP are considered markers of heart failure. This examination is also indicated to help establish the diagnosis, monitoring, and prognosis of heart failure. Natriuretic peptide examination can be done by several methods such as radioimmunoassay (RIA), Enzyme immunoassay (EIA), Fluorescence immunoassay (FIA), and Sandwich Electro Chemiluminescence Immuno Assay (Sandwich ECLIA).
Term Document Frequency (TDF) Method for Extracting User Posts and Emerging Events in Social Networks

Social network is a place where people exchange and share data related to the current trends and events all over the world. This specific behavior of users made us concentrate on the logic that processing these data may lead us to the extracting the current topic of curiosity between the users. Applying data clustering technique like Term-document-Frequency (TDF) based approach over these data may leads us up to the mark but there will be little chance of negatives. We are going to do a likely medium that can give both usual mentioning behaviour of a consumer and also the frequency of users occurring in their mentions. It also works well even the data of the messages are very small information. These extracted emerging topic are shown to the user those who subscribe for the details.
Multi-Document Abstractive Summarization using Recursive Neural Network

Text summarization is an area of research with a goal to provide short text from huge text documents. Extractive text summarization methods have been extensively studied by many researchers. There are various type of multi document ranging from different formats to domains and topic specific. With the application of neural networks for text generation, interest for research in abstractive text summarization has increased significantly. This approach has been attempted for English and Telugu languages in this article. Recurrent neural networks are a subtype of recursive neural networks which try to predict the next sequence based on the current state and considering the information from previous states. The use of neural networks allows generation of summaries for long text sentences as well. The work implements semantic based filtering using a similarity matrix while keeping all stop-words. The similarity is calculated using semantic concepts and Jiang Similarity and making use of a Recurrent Neural Network (RNN) with an attention mechanism to generate summary. ROUGE score is used for measuring the performance of the applied method on Telugu and English langauges
Enhancing Students’ Speaking Ability Through Small Group Discussion Technique to the Firts Year Students of SMA Negeri 1 Ratahan

This research in intended to find out the effectiveness of small group discussion technique in improving the students’s speaking ability. It was conducted at SMA Negeri 1 Ratahan in which one class of the first-year students of the school was the sample. The data of the research were obtained by using test in the form of pre-test and post-test. The result showed that the scores of the post-test were higher than that of the pre-test. The mean of the post-test is 8.2 and the mean of the pre-test is 6.7. Teaching speaking skill by using small group discussion technique can improve the students’ ability in speaking. Small group discussion technique can give the students opportunity to practice their language. In small group discussion, they can express their ideas and thought freely. It will be better for English teacher to vary the techniques of teaching to avoid boredom that might appear to the students.
Full Issue

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 56, Issue 1 p. I-I Full Issue Full Issue First published: 06 March 2019 https://doi.org/10.1111/j.1467-6346.2019.08728.xAboutPDF 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 onFacebookTwitterLinkedInRedditWechat Volume56, Issue1March 2019Pages I-I RelatedInformation
A One-shot Learning Approach to Image Classification using Genetic Programming

In machine learning, it is common to require a large number of instances to train a model for classification. In many cases, it is hard or expensive to acquire a large number of instances. In this paper, we propose a novel genetic programming (GP) based method to the problem of automatic image classification via adopting a one-shot learning approach. The proposed method relies on the combination of GP and Local Binary Patterns (LBP) techniques to detect a predefined number of informative regions that aim at maximising the between-class scatter and minimising the within-class scatter. Moreover, the proposed method uses only two instances of each class to evolve a classifier. To test the effectiveness of the proposed method, four different texture data sets are used and the performance is compared against two other GP-based methods namely Conventional GP and Two-tier GP. The experiments revealed that the proposed method outperforms these two methods on all the data sets. Moreover, a better performance has been achieved by Naïve Bayes, Support Vector Machine, and Decision Trees (J48) methods when extracted features by the proposed method have been used compared to the use of domain-specific and Two-tier GP extracted features. © Springer International Publishing 2013.
Analyzing Security of Single Sign on System through Advanced Encryption Standard 

Single sign-on mechanisms allow users to sign on only once and have their identities automatically verified by each application or service they want to access afterward. Most of current application architectures require the user to memorize and utilize a different set of credentials (e.g., username/password or tokens) for each application he/she wants to access. In this paper, however, it is shown that their scheme is actually insecure as it fails to meet security during communication. This paper illustrates the Chang & Lee scheme and it aims to enhance security using AES encryption and decryption. The Advanced Encryption Standard (AES) is a specification for the encryption of electronic data recognized by the U.S. National Institute of Standards and Technology. It is expected to become the accepted means of encrypting digital information, telecommunications, including financial, and government data.
Robust Sparse Transfer Learning for Image Classification

Transfer learning aims to transfer the knowledge learned from the source to the target data. However, noise-corrupted target data may limit the transfer learning capability. Thus, removing the noise in the data is essential to improve transfer learning performance. This paper proposes robust sparse transfer learning (RSTL) to improve the robustness of transfer learning. The RSTL uses noise-removed target domain data for project learning, where the employed nuclear norm ensures that the clean data matrix and the coefficient matrix are low-rank. The L norm is also adopted to ensure the sparsity of the target domain noise. Further, a reconstructive term is used, which aims to learn a reconstruction coefficient matrix. Extensive experimental evaluations on four datasets verify the promising ability of the proposed method compared with the other methods.
Validating of organizational leadership assessment in postsecondary education

The present study validates the organizational leadership assessment (OLA) instrument.The OLA questionnaire has been widely used in Western countries, and it has also been used in non-western countries.We translated the OLA into Bengali and administered this to 570 post-secondary students.Specifically, it examines the feasibility of its use with Bengali Medium students in West Bengal, India.The Principal Component Analysis (PCA) retained a six-factor solution with a satisfactory psychometric reliable research instrument (OLA).The psychometric features of OLA supported its feasibility as a sound and reliable research instrument to measure students' perception of teacher's Servantleadership behavior in the context of West Bengal.
The study of the 24 January 2020 Elazig-Sivrice earthquake in the eastern Turkey.

The present study examines the 24 January 2020 Elazig-Sivrice earthquake by jointly trying to model quasi co-seismic static surface displacements from InSAR and highfrequency co-seismic data from seismological networks at local, regional and teleseismic distances to retrieve source parameters of the mainshock.Furthermore, the authors claim that they estimated moment tensor for 18 fore-/after-shocks with Mw ≥ 4.3 based on the modelling of the regional broadband data.The authors declare and highlight that the mainshock partially ruptured a seismic gap.Although the current work examines an important event occurred recently in the region, I do have problems with
The Use of the Instagram Platform and Text Messengers in the Context of Contemporary Education.

Our research is aimed at the identifying the particularities of teaching foreign languages by means of interactive applications such as Instagram and text messengers (specifically Whatsapp). In this article we distinguished the main advantages of the present applications: spatial intelligence, inclusiveness and the element of permanent presence in the learning process, the possibility of transferring a part of classroom teaching into online space, the motivation of the profile, the linguistic means used for encouraging individuals to be more active and keen while learning foreign languages.Moreover, we pointed out the problems of time-management and time refocusing in the learning process. Despite the fact that there are many obvious advantages of the Instagram and text messengers we have identified the obstacles, which can influence the quality of the learning process. Particularly, we highlighted the problem of assessment and the monitoring of the material and the professionalism of the teacher who is running the Instagram profile.
Professional Components

To further reduce the amount of code for Web Components I suggest some smart enhancements. By using decorators you can make the code even easier to read. That’s the power of TypeScript. All examples in this chapter are written in TypeScript.
AN ANALYSIS OF STUDENTS’ WRITING ASSIGNMENT OF ANALYTICAL EXPOSITION TEXT

Writing is not always easy to do. The students face some difficulties in mastering writing skill because they need particular practice to develop their writing skill. The teacher should know the students’ abilities and difficulties toward this skill and one of many ways teacher can do is by analyzing students’ compositions. In this research, they are generic structures and language features of analytical exposition texts. They may make students find some difficulties in analytical exposition texts.&#x0D; This study is descriptive qualitative study and this research is aiming to describe the students’ competence in writing expository text. The researcher is the first instrument and the second instrument for this study is the students’ compositions of analytical exposition texts. To analyze the data, there will be three steps; classification, analysis, and representing to determine whether the students write analytical exposition text with proper generic structures and language features or not.&#x0D; After being analysis, the researcher found that the students could write analytical exposition texts with a good generic structures and language features. However, there are some students who do not compose them properly. For generic structures, some students often do not write review of arguments in thesis and reiteration. And for language features, some of the students often do not apply the diction well. The students are proficient enough in organizing analytical exposition text in term of generic structures and language features.&#x0D; From the analysis, the abilities and difficulties of the students can be identified by the teacher. The teacher should give clear explanation and understanding in teaching analytical exposition text. The teacher had to explain about how to make analytical exposition text deeply in order that the students could comprehend the text well. In addition, the English teacher could give comments to the students’ composition for the better next writing assignments, because they will know about the mistakes that they still made.&#x0D; Keywords: analytical exposition text, generic structures, language features, writing
NEA Creative Forces: Clinical Component (NEA)

Federal Grants & ContractsVolume 43, Issue 23 p. 1-1 Grant Alerts NEA Creative Forces: Clinical Component (NEA) First published: 06 November 2019 https://doi.org/10.1002/fgc.30721Read 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 onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume43, Issue237 November 2019Pages 1-1 RelatedInformation
Euclidean geometry

This textbook is a comprehensive introduction to the key disciplines of mathematics - linear algebra, calculus, and geometry - needed in the undergraduate physics curriculum. Its leitmotiv is that success in learning these subjects depends on a good balance between theory and practice. Reflecting this belief, mathematical foundations are explained in pedagogical depth, and computational methods are introduced from a physicist's perspective and in a timely manner. This original approach presents concepts and methods as inseparable entities, facilitating in-depth understanding and making even advanced mathematics tangible. The book guides the reader from high-school level to advanced subjects such as tensor algebra, complex functions, and differential geometry. It contains numerous worked examples, info sections providing context, biographical boxes, several detailed case studies, over 300 problems, and fully worked solutions for all odd-numbered problems. An online solutions manual for all even-numbered problems will be made available to instructors.
Delphi Technique Based Project Performance Framework for Mobile Phone Usage in Agricultural Practices

Agriculture plays a significant role for economic and social development in most undeveloped countries.Information of adequate quality is a necessary condition for improvement of all areas of agriculture (Stoica & Brouse, 2013).With the rapid development of Information and Communication Technologies (ICTs), data and information can be effectively generated, stored, analyzed, disseminated and used to support farmers and farming communities to improve agricultural productivity and sustainability.Information services for farmers at the national and regional level are a promising new field of research and application in the emerging field of e-agriculture.The development of ICT projects have increased in many organizations to ensure that overall needs of customers in business requirements are fulfilled.However, many ICT projects failed to take off such as a series studies (Ashraf, Sarfraz & Mohsin, 2010;Stoica & Brouse, 2013) produced.Stoica and Brouse (2013) states that due to the ICT project failure and its impact to the organization, researchers and practitioners are asked to specifically look at the history of how the project is carried out to find an effective approach and comprehensive to overcome this issue.Despite of having a lot of standard on project management methodologies in ICT, however up to most ICT project have yet to show a good track record of success (Marchewka, 2010).As far as ICT project management tools for agriculture is concerned, farmers need to access information about new technologies before they can consider adopting them and thus look up to research and extension agents as sources of new technologies.Access to appropriate information and knowledge is an overriding factor for successful agricultural production and thus rural development.However, the traditional approach of providing agricultural information through extension services is
Probability Theory

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MIXED CODE THAT ENTERENCHED IN THE LEARNING PROCESS BY CHATHOLIC JUNIOR HIGH SCHOOL GONZAGA TOMOHON

The teaching of second language or the third make sociolinguistic problem. For most Indonesian people, Indonesian language is the second or third language. The teaching of of Indonesian language is integrated in Indonesian language subject that starts from elementary to high school. Indonesian language is a main language in Indonesian especially in education institutes. It is undebieble fact that students use another language at Gonzaga Junior High School Tomohon because of the influence of social and culture background. Code mixing is caused by some factors, namely (1) subject, (2) describing, (3) daily routine in teaching and learning activities in Junior High School Catholic Gonzaga Tomohon has been the main issue in their research.This research is aimed to explain about kinds of code mixing and factors that cause the code mixing in teaching and learning activities by Junior High School Students Catholic Gonzaga Tomohon.Theories used for this research is the theory of speech community, bilingual theory , theory of code and code mixing. This research is a descriptive qualitative. The research data is done with the following method of observation technic. The data in this research is the student speech that contains code mixing. The data analysis that use is qualitative analysis with equal method.The result of this research shows that speech act of the students in Gonzaga Junior High School of Tomohon found code mixing. The form of code mixing that using are Indonesian, English and Manado Malay. Based on the result of this research can concluding that kinds of code mixing are code mixing in lexical form, frasa form and clausa form. The factors of code mixing are namely, describing and daily routine.&#x0D; Key words: code mixing, teaching and learning activities, Indonesian language, sociolinguistic
Searching

Search is the most basic and fundamental operation of computers. It plays a vital role in areas like artificial intelligence, machine learning, deep learning, and a variety of applications. We examine the role of searchSearch in several related topics in this chapter.
Variable-Length Particle Swarm Optimization for Feature Selection on High-Dimensional Classification

© 1997-2012 IEEE. With a global search mechanism, particle swarm optimization (PSO) has shown promise in feature selection (FS). However, most of the current PSO-based FS methods use a fix-length representation, which is inflexible and limits the performance of PSO for FS. When applying these methods to high-dimensional data, it not only consumes a significant amount of memory but also requires a high computational cost. Overcoming this limitation enables PSO to work on data with much higher dimensionality which has become more and more popular with the advance of data collection technologies. In this paper, we propose the first variable-length PSO representation for FS, enabling particles to have different and shorter lengths, which defines smaller search space and therefore, improves the performance of PSO. By rearranging features in a descending order of their relevance, we facilitate particles with shorter lengths to achieve better classification performance. Furthermore, using the proposed length changing mechanism, PSO can jump out of local optima, further narrow the search space and focus its search on smaller and more fruitful area. These strategies enable PSO to reach better solutions in a shorter time. Results on ten high-dimensional datasets with varying difficulties show that the proposed variable-length PSO can achieve much smaller feature subsets with significantly higher classification performance in much shorter time than the fixed-length PSO methods. The proposed method also outperformed the compared non-PSO FS methods in most cases. © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.