Reviewerly/exHarmony huggingface dataset:
IMPROVING INTERACTION AND COMMUNICATION IN UNIVERSITY STUDENTS THROW THE USE OF MOBILE APPS

Appears in: ICERI2019 Proceedings Publication year: 2019Pages: 9098-9105ISBN: 978-84-09-14755-7ISSN: 2340-1095doi: 10.21125/iceri.2019.2189Conference name: 12th annual International Conference of Education, Research and InnovationDates: 11-13 November, 2019Location: Seville, Spain
Extending Quantum Links: Modules for Fiber- and Memory-Based Quantum Repeaters.

We analyze elementary building blocks for quantum repeaters based on fiber channels and memory stations. Implementations are considered for three different physical platforms, for which suitable components are available: quantum dots, trapped atoms and ions, and color centers in diamond. We evaluate and compare the performances of basic quantum repeater links for these platforms both for present-day, state-of-the-art experimental parameters as well as for parameters that could in principle be reached in the future. The ultimate goal is to experimentally explore regimes at intermediate distances, up to a few 100 km, in which the repeater-assisted secret key transmission rates exceed the maximal rate achievable via direct transmission. We consider two different protocols, one of which is better adapted to the higher source clock rate and lower memory coherence time of the quantum dot platform, while the other circumvents the need of writing photonic quantum states into the memories in a heralded, non-destructive fashion. The elementary building blocks and protocols can be connected in a modular form to construct a quantum repeater system that is potentially scalable to large distances.
A Study on the Word Recognition Teaching Methods to Activate Right Brain – Focus on Semantic Elements of Characters

Korean learners who want to learn Chinese have more difficulty in reading and writing than listening and speaking in the learning process because Chinese characters become optional subject in Korean educational curriculum and there is no chance to expose them and learners become lack of basic Chinese character background. Even if they had taught Chinese education in high school, Chinese learners who don’t have enough experience in learning Chinese characters in the Chinese Pinyin-oriented curriculum introduce the English learning methods as it is.BR A phonogram, English, has fundamentally different character traits from a ideogram, Chinese characters. Therefore, a differentiated approach is required from the word recognition process which is the beginning of literacy. However, most of Korean education combines literacy education focusing on research performance or theories of English in the common area of language.BR Thus this study attempts to consider from a new perspective called ‘brain functional aspect’ in order to understand the literal characteristics of Chinese characters and find ways to effectively recognize the meanings of characters. China has already included Chinese character education into a whole brain education and has gone so far as to commercialize teaching methods for activating the right brain function centered on the semantic elements of Chinese characters. On the other hand, Korean education is unfamiliar with the study of brain function of existing teaching methods or brain-friendly methods.BR The purpose of this study is to provide a stepping stone for the study of Chinese education on ‘brain function’ by examining the brain functional characteristics of Chinese characters based on the above contents and considering the methods of how learners can use the right brain function to recognize characters. As a result, we found that the phonogram and ideogram differs in functional areas of the brain through medical research and examined how the word recognition teaching can be developed to cause the activation of the right brain function based on the elements of characters, forms and meanings by analyzing the brain functional features of Chinese characters.
Efficient Technique to Accelerate Neural Network Training by Freezing Hidden Layers

Deep neural networks have the least parameters in early layers but it take up very complex and long computation. This paper propose a method in which a set number of training run are used to train the hidden layers of neural networks. The hidden layers are freezing out one by one and excluding from backward pass. Several experiments are carried out on CIFER; we practically show that Freeze Out technique gives 3% loss in accuracy for DenseNets while saving of up to 20% wall-clock time during training, with no loss of accuracy for ResNets while speed up to 20% and no improvement for VGG networks.
MobilePill: Accurate Pill Image Classification via Deep Learning on Mobile

It is cumbersome for older people to search for prescription drugs via the Internet. Thus, recent studies use mobile to help this inconvenience. One of them is to provide the details of pill information prescribed through mobile. However, previous studies have shown many difficulties in providing drug information through mobile. In particular, it is more challenging to provide the pill information after classifying drug image in terms of accuracy. In this paper, we tackle the problem of accuracy, whether a given pill image is correctly classified via mobile phone. In this circumstance, we develop an approach that uses a hybrid CNN model to classify various pill images. This model adopts approaches to classify different properties in pill images with the same shape. In reality, we designed a system called “MobitePitt,” which is a hybrid model with each different independent model, and have each different training sets according to dosage forms. In extensive experiments, “MobitePitt” achieved 73.39% accuracy for the case of one-sided, which was 39.25% higher than previous models. This result provides the possibilities that can be applied in real-world.
Proceedings of the Trends in Forensic Sciences (TIFS) Conference 2019

The Annual Trends in Forensic Sciences Conference was pioneered by Forensics Program Chair – Dr. Shashi Jasra six years ago with an aim of gathering experts in the forensics world and students with a vested interest in it at the same conference to showcase the opportunities and growth in the field. Every year the conference is an educational and interactive day-long event full of multidisciplinary presentations, hands-on forensics workshops and a research showcase for new UWindsor Forensics graduates to exhibit their thesis projects
A fuzzy learners’ knowledge modelling system for online learning

Many past studies report on personalising learning via intelligent systems but only a handful report on assisting instructors in personalising learning by leveraging technology. Instructors are knowledgeable in teaching and learning but they seldom put much effort to personalise learning due to the complexity of this approach. This study presents a fuzzy learners’ knowledge modelling system that addresses three issues related to the complexity of personalising learning. This study also demonstrates how this system can be applied in a real-world scenario. The case study shows that based on learners’ performance in online assessments, this system is able to assist instructors to personalise learning by planning for appropriate interventions through the insights derived from the system.
Penerapan Model Pembelajaran Project Based Learning untuk Meningkatkan Keterampilan Oral Communication Peserta Didik Kelas X MIPA 4 SMA Negeri 5 Surakarta

The aim of this research was to determine the improvement of oral communication skills through the PjBL learning model of class X MIPA 4 Surakarta Public High School 5. The research subjects used were students of class X MIPA 4 consisting of 32 students. Research is classroom action research (CAR) based on problems that occur in the class. Data and sources of research data about oral communication skills obtained through observation sheets, closed interviews with teachers and students, and documentation using the PjBL learning model. Data collection by conducting observations, interviews, and documentation.Validation of data using triangulation techniques include observation, interviews, and documentation. Data analysis techniques are done by data reduction, data presentation, and conclusion drawing. The results of the research conducted concluded that the application of the PjBL learning model in learning activities of Kingdom Animalia material using projects showed that there was an increase in oral communication components of students by 40% so that oral communication skills of students increased to 60% -72.31%.
Analysis of Grammatical Errors in Three Selected Nigerian Newspapers

The high incidence of grammatical errors in the Nigerian print media has become a matter of great concern to the academia because of the great damage it does to the reading public. This research work sets out, essentially to identify, describe, analyze and correct obvious grammatical errors in three selected widely read Nigerian newspapers namely: The Sun, The Vanguard and The Guardian. Using the qualitative research method, 30 copies of each of the newspapers, randomly selected from Jan. 2005 to July 2018 editions were examined to identify any grammatical error, guided by the tenets of Transformational Generative Grammar of Noam Chomsky. The data gathered were analyzed using the Error Analysis procedure of Stephen Pit Corder. For ease of assessment, the errors were classified into lexical, syntactic and semantic categories and the analyses were presented in form of narrative. The findings showed that grammatical errors in the newspapers were as a result of personal native language habits (patterns and rules), socio-economic influences and outright abuse of journalese. To stem the ugly trend, the researcher recommends that English language (Grammar) should be made a compulsory course in journalism and Mass Communication; editors should wake up to justify their primary duty of gate-keeping and policing of both content and presentation of information; and that print media organizations should adopt good feedback mechanism for improved and error free expressions.
Social Media Attributions in the Context of Water Crisis

Attribution of natural disasters/collective misfortune is a widely-studied political science problem. However, such studies are typically survey-centric or rely on a handful of experts to weigh in on the matter. In this paper, we explore how can we use social media data and an AI-driven approach to complement traditional surveys and automatically extract attribution factors. We focus on the most-recent Chennai water crisis which started off as a regional issue but rapidly escalated into a discussion topic with global importance following alarming water-crisis statistics. Specifically, we present a novel prediction task of attribution tie detection which identifies the factors held responsible for the crisis (e.g., poor city planning, exploding population etc.). On a challenging data set constructed from YouTube comments (72,098 comments posted by 43,859 users on 623 relevant videos to the crisis), we present a neural classifier to extract attribution ties that achieved a reasonable performance (Accuracy: 81.34\% on attribution detection and 71.19\% on attribution resolution).
The Effect Breakfast Of Energy Intake On Learning Concentration Level Among Islamic Boarding School Students

Background: Concentration was a critical element on learning process, and it is absolutely requires on learning. The factors that influence concentration of learning is hunger. These symptoms are usually experienced by students did not have breakfast before enter the class.Objective: This research was to analyze the effect of  breakfast energy intake on learning concentration level among Islamic Boarding School students. Method: This study an observational study with a cross-sectional design. The research was conducted in Islamic  Boarding schools Darussalam Gontor 2 for Girls in East Java , Mantingan, Indonesia. The research was conducted within three months, calculated December 26th, 2018 to February 28th, 2019. Result: The student's intakes staple food (rice), vegetables and animal protein, vegetables, and snacks. They had seven days menu cycle. Their energy intake is 1194,9 kcal, 43% of respondent got enough calories and 57% had fewer calories. Level of concentration most responden 54,7 % had medium, 42,8 % had good and the rest was bad. There was significant correlation between breakfast and concentration p.value 0,04 < 0,05. Conclusion: There was the effect of breakfast energy intake on learning concentration level among students islamic boarding school. Keyword: adolescents,  calorie of breakfast, concentration of learning
Control of an inverted pendulum electric wheelchair by body movement

This study investigated the development and control of an inverted pendulum electric wheelchair that can move forward and backward and can rotate according to the movement of the user’s center of gravity, without requiring use of the hands. The wheelchair is moved forward and backward by means of an integrated gyro + accelerometer that monitors shifts in the user’s center of gravity. Left/right rotation is controlled according to the difference in air pressure between the right and left sides of an air cushion placed on the seat surface. Also, we introduced cam mechanism that cam push up the wheelchair and make it possible to get over the step.
Reasons Why Businesses Should Print Their Own Checks

Are you a business owner who wants to easily cut down on your weekly or monthly expenses? We will be giving you a few reasons why you should consider ...
Guides: Video Resources: Streaming Databases and Collections

RRC Library offers thousands of educational videos, documentaries and feature films. Learn more about our video collection here. Learn about licensed video databases and streaming collections available from the Library.
Proposal to Implement the Precalculus and Basic Mathematics Courses Using an Intelligent Tutoring System

During 2017 and 2018, the Precalculus course at the Technological University of Panama was offered via an intelligent tutoring system (ITS). Analysis of the results show that student interaction with the ITS learning modules contributes to the levelling of knowledge and to improved performance in mathematics. As a by-product of this implementation, a proposal called "Remedial Action Program" (Spanish acronym, PAR), is presented in this article, the purpose of which is to take advantage of STI's to level students' mathematical knowledge, thereby improving their chances to be admitted to, and retained in, the UTP. This proposal is structured around three programs for students with different mathematics profiles.
a, the Sistem Pendukung Keputusan Pencarian Universitas di Malang Menggunakan Weight Product dengan Pembobotan Weighted Sum Model

Decision Support System (DSS) is a system that can help someone in making a decision to solve a problem. Weighted Sum Model (WSM) method and Weighted Product (WP) method are used in this system. The WSM method is the sum of the attribute rating multiplications with attribute weights. In this system, WSM method is used as a weight and will be used on the WP method. This weight is filled manually by the user and then calculated by the WSM method. Whereas the Weighted Product (WP) method is a method that uses multiplication to connect attribute ratings, and the rating must be raised first with the weight of the attribute. This system is used in the selection of college in the city of Malang. In the search process there are several criteria used, namely the number of computer department, tuition fees, campus environment, the number of scholarship programs and accreditation. These criteria are used as a reference for college grades used in the assessment section. The search procedure start when a user enters a criteria value that has been determined by the user. Furthermore, the value of the calculation is compared with the value already on data pattern. To find out whether the chosen university matches with the entered criteria, weight of criteria must be checked based on the university chosen by the user. The conversion value from input are compared by the value in the pattern data. The testing process in this study is by using a confusion matrix. Based on testing using the method confusion matrix, researchers obtained 72.50 % value of accuracy, 82,76% value of precision, 80% value of recall and 81,36% value of f-measure.
Library Guides: Music performance: percussion: Home

Welcome to the research guide for Percussion, a starting point for finding journal articles, books, data and more!
Quantum computer IonQ raises funds

IonQ, a quantum computer start-up based in College Park, Maryland, has closed a $55 million funding round. Led by Samsung Catalyst Fund and Mubadala Capital, the round brings IonQ’s total funding to $77 million. IonQ is applying the trapped-ion approach to developing practical applications of the superfast computing technique. Firms including Google, IBM, and Microsoft are also vying to build quantum computers that operate millions of times as fast as current high-volume computing systems.
LibGuides: Management of Engineering and Technology: Learn the Library Business

This guide is for the NCU Management of Engineering and Technology specialization. It contains resources available in the NCU Library.
Muatan Konten Lokal pada Materi Pelajaran Bahasa Inggris di SMP Negeri 5 Sigi

Based on the 2013 curriculum 2016’s revision, there are subject materials that demand about local content in English subjects at the level of SMP Class VII. Teachers need many researches and practices integrating and implementating these subjects. Basically, it needs to be done in-depth study in the form of content analysis. This research was conducted on content and learning English in SMP Negeri 5 Sigi. This study aims to find out 1) how many percentage of local content in English lesson material Class VII SMP in the curriculum 2013 revision 2016; 2) how to integrate local content in English subject matter in SMP Negeri 5 Sigi; 3) how the implementation of material with local content in English learning in SMP Negeri 5 Sigi, and; 4) how to integrate local content in effective and efficient English lessons in SMP Negeri 5 Sigi. The study used a qualitative descriptive approach with the method of collecting document studies, interviews, and observation. The research results are 1) the proportion of local content that can be integrated into English language learning material SMP is 95%; 2) the integrity of local content in English learning materials in SMP Negeri 5 Sigi can be found in the lesson plan; 3) implementation of materials with local content in English learning attached to KTSP, Syllabus, lesson plan and learning resources enrichment book.
IMPLEMENTASI KEBIJAKAN BANTUAN OPERASIONAL SEKOLAH DAERAH (BOSDA) DI SEKOLAH MENENGAH PERTAMA NEGERI 02 KABUPATEN MALINAU

The purpose of this study was to describe and analyze the Implementation of District School Operational Assistance Policy (BOSDA) at Junior Secondary School 02 Malinau City. The research method used is descriptive qualitative. The data analysis used is the interactive data model. The result of the research, it can be concluded that Operational Assistance Policy of School Area in Junior Secondary School of State 02 Malinau as regulated in Decision of Regent of Malinau Number 25 year 2014, immensatively less than optimal, because confronted by various obstacles. Keywords: Implementation, Policy, School Operational Assistance
TOPIC EXTRACTION OF CRAWLED DOCUMENTS COLLECTION USING CORRELATED TOPIC MODEL IN MAPREDUCE FRAMEWORK

The tremendous increase in the amount of available research documents impels researchers to propose topic models to extract the latent semantic themes of a documents collection. However, how to extract the hidden topics of the documents collection has become a crucial task for many topic model applications. Moreover, conventional topic modeling approaches suffer from the scalability problem when the size of documents collection increases. In this paper, the Correlated Topic Model with variational Expectation-Maximization algorithm is implemented in MapReduce framework to solve the scalability problem. The proposed approach utilizes the dataset crawled from the public digital library. In addition, the full-texts of the crawled documents are analysed to enhance the accuracy of MapReduce CTM. The experiments are conducted to demonstrate the performance of the proposed algorithm. From the evaluation, the proposed approach has a comparable performance in terms of topic coherences with LDA implemented in MapReduce framework.
The Effects of Recording Distance and Viewing Distance on Presence, Perceptual Characteristics, and Negative Experiences in Stereoscopic 3D Video

The study explores the effects of recording and viewing distances in stereoscopic 3D on presence, perceptual characteristics, and negative experiences. Groups of 20 participants were randomly assigned to each of the three viewing distances, and all participants were exposed to five versions of the stereoscopic 3D music video that differs in recording distance. The results showed that first, viewers felt a higher experience of presence and had a better perception of objects positioned near the cameras. Second, viewers felt a greater perception of screen transmission as the viewing distance increased. Finally, viewers felt a greater negative experiences due to the joint effects of recording and viewing distance. As investigating the influence of stereoscopic 3D content and viewing environments on psychological factors, the study expects to provide a guideline of human factors in 3D.
Workflow Scheduling in Cloud Computing Environment using Hybrid CSO-DA

With advances in virtualization technology, cloud computing has become the most powerful and promising platform for business, academia, public and government organizations. Scheduling these workflows and load balancing to get better success rate becomes a challenging issue in cloud computing. In this paper, we used Cats and Dragonfly Optimization (CSO-DA) algorithm to balance the Load in the process of allocating resources to virtual machines in cloud computing in order to improve the speed and accuracy of scheduling. The proposed method consists of the following steps: initialization of the algorithm and cloud computing, determining the number of virtual machines and the number of tasks, implementing a dragonfly optimization algorithm for choosing the best host and implementing a cat collapse algorithm for balancing the load and Schedule tasks between virtual machines. Our experiments show that as far as run time, response time, task immigration and significant load balances are concerned, our proposed model combining cat and dragonfly optimization algorithms achieved better performance in allocating resources and load balance between virtual machines than other methods.
LibGuides: Hekman Library for Seminary Distance Education: Getting Help

Librarian-crafted guide to services and resources in Hekman library for Calvin Seminary Distance Education students
Model based joint target tracking and classification with RCS measurement

A model-based joint tracking and classification (JTC) method is proposed for narrowband radar with kinematic and radar cross section (RCS) measurements. The method is derived from the 3D scattering center model (3DSCM), which can construct an explicit relation between the aspect angle and the predicted RCS. To deal with the numerical problem in observation model, a modified likelihood function for RCS measurement is adopted under the assumption of additive Gaussian observation noise. The JTC processing is realized by sequential Monte Carlo (SMC) technique. Specifically, a bank of particle filters are used to obtain type-dependent target state and type estimates. Compared with the traditional JTC methods using low resolution sensor, the proposed method is free from the constraint that target classification has to rely on different maneuvering modes. Simulation results validate the effectiveness of the proposed method with maritime application scenario.