Reviewerly/exHarmony huggingface dataset:
Students’ Problems in Completing Sentence by Using Linking Be at First Grade of SMPN 1 Kerinci

One of the rules of grammar carries out important rule that is using simple linking be. Linking Be shows existence or, as the case may be, nonexistence. This research was aimed to find out the students’ problems in completing sentence by using linking be at first grade of SMPN 1 Kerinci Academic Years 2018/2019 and the causes of the students’ problems in completing sentence by using linking be at first grade of SMPN 1 Kerinci Academic Years 2018/2019. The design of this research was descriptive research. The population was at the grade VII students of SMPN 1 Kerinci. There were 156 students which consisted of 7 classes as the population. This population was tested by using Bartlett test to make homogeneity. Then, the sample was VII B. The instruments were given grammar test in multiple choices as quantitative data and took interview as qualitative data. Moreover, it was also proven by the result of the total percentage of the students. There were 47% students who got very good, 26% students got good, 21.7% students got fair, 4.3% got weak and no student got poor And mean score of the students was 75.6. Based on interview to students, there were some problems faced by the students’ in completing sentence by using linking be. They only made mistake in some cases. But they have learned and known which one to be is when they were asked to make sentence. Based on the result of data analysis, it was concluded that generally the students’ students’ problems in completing sentence by using linking be at first grade of SMPN 1 Kerinci was good.
Academic Words in the English Research Article Abstracts: the Coverage and Frequency

The present study aimed at exploring the abstracts of research articles written by non-native English researchers to uncover the specific characteristics of academic vocabulary employed in the English research articles abstracts.It focuses on frequency and coverage distribution of the words from the Academic Word List (Coxhead, 2000) in the abstracts of research articles. The source of data for this corpus study was gathered from 97 abstracts written by the EFL researchers and published by the Journal Pendidikan dan Kebudayaan Missio at STKIP St. Paulus Ruteng from 2015 until 2018. The results of this study revealed that the coverage of K1, the first most frequent 1000 English words, is the most dominant lexical items applied by the researchers. It covered 71.33% of the texts. The representation of lexical items that belong to K2, the second most frequent 1000 English words, covered 5.44% of all the words used by the writers in their abstracts. Moreover, the presence of Academic Word List, which refers to a list of 570 word families that are commonly found in academic texts and Off-list, which refers to the words that do not belong to K1 or K2 because it is related to certain field, has slight difference over all of the texts where the former covers 11.95% and the later covers 11.26%. As far as the findings of the present study are concerned, the room for some improvements on academic words applied in the abstracts need to pay attention.
LA SCIENZA DEI DATI: UNA NUOVA SFIDA MULTIDISCIPLINARE

The present manuscript aims to delineate and deepen the new multidisciplinary challenge of Data Science. In order to make the reader aware of the revolutionary scope of this new discipline, I will review various examples of success arising from the analysis of so called â€œBig Dataâ€. My analysis will not fail to underline the economic and social impact of the Big Data revolution by also referring to the ethical issues that naturally arise in the presence of sensitive data and information.
A METHOD FOOTBALL TEAM MODEL OPTIMIZATION AND APPLICATION OF THE OPTIMIZATION CONTROL

The development of the AI, IoT, and Big Data have to become strongly apply to discrete event strings systems. That are modern developments of the world. Therefore, we have to have an advanced method to develop adaptive applications, especially with MIMO discrete event systems. There is a limit while using a continuous calculation to control systems because the big calculation is an obstacle. So we have to find an optimization method to reduce the number of parameters in the calculation at any time. We could do it by choice the main parameters and except auxiliary parameters. In this paper, we introduce a Football Team Optimization (FTO) method, which is a new method to do optimization problem while control with many parameters system. The application and analysis to compare any method as PSO, traditional PID, which takes out the difference of this algorithm.
A Novel Distributed Duration-Aware LSTM for Large Scale Sequential Data Analysis

Long short-term memory (LSTM) is an important model for sequential data processing. However, large amounts of matrix computations in LSTM unit seriously aggravate the training when model grows larger and deeper as well as more data become available. In this work, we propose an efficient distributed duration-aware LSTM(D-LSTM) for large scale sequential data analysis. We improve LSTM’s training performance from two aspects. First, the duration of sequence item is explored in order to design a computationally efficient cell, called duration-aware LSTM(D-LSTM) unit. With an additional mask gate, the D-LSTM cell is able to perceive the duration of sequence item and adopt an adaptive memory update accordingly. Secondly, on the basis of D-LSTM unit, a novel distributed training algorithm is proposed, where D-LSTM network is divided logically and multiple distributed neurons are introduced to perform the easier and concurrent linear calculations in parallel. Different from the physical division in model parallelism, the logical split based on hidden neurons can greatly reduce the communication overhead which is a major bottleneck in distributed training. We evaluate the effectiveness of the proposed method on two video datasets. The experimental results shown our distributed D-LSTM greatly reduces the training time and can improve the training efficiency for large scale sequence analysis.
IRIS CONTROLLED SMART WHEELCHAIR

Paralysis or blindness is considered as a major curse in this world. The number of persons who are paralyzed and therefore dependent on others due to loss of self-mobility is growing with the population. Quadriplegia is a form of Paralysis in which you can only move your eyes. Much work has been done to help disabled persons to live independently. In this project, we are interested in iris biometric applications. More precisely, our contribution consists in designing both a pupil detection and a tracking procedure from images acquired by low-cost webcams. The novelty of our approach relies on the fact that it is operational even with a minimal user cooperation and, under bad illuminations and acquisition conditions. A robust classification algorithm called the Viola Jones algorithm is designed to detect the face as well as the pupil. Experimental results are performed in order to evaluate the performances of the proposed detection and tracking system.
Rapid Sequence Matching for Visualization Recommender Systems

We present a method to support high quality visualization recommendations for analytic tasks. Visualization converts large datasets into images that allow viewers to efficiently explore, discover, and validate within their data. Visualization recommenders have been proposed that store past sequences: an ordered collection of design choices leading to successful task completion; then match them against an ongoing visualization construction. Based on this matching, a system recommends visualizations that better support the analysts' tasks. A problem of scalability occurs when many sequences are stored. One solution would be to index the sequence database. However, during matching we require sequences that are similar to the partially constructed visualization, not only those that are identical. We implement a locality sensitive hashing algorithm that converts visualizations into set representations, then uses Jaccard similarity to store similar sequence nodes in common hash buckets. This allows us to match partial sequences against a database containing tens of thousands of full sequences in less than 100ms. Experiments show that our algorithm locates 95% or more of the sequences found in an exhaustive search, producing high-quality visualization recommendations.
Understanding Urgency in Radiology Reporting: Identifying Associations Between Clinical Findings in Radiology Reports and Their Prompt Communication to Referring Physicians.

In this study, we aim to develop an automatic pipeline to identify clinical findings in the unstructured text of radiology reports that necessitate communications between radiologists and referring physicians. Our approach identified 20 distinct clinical concepts and highlighted statistically significant concepts with strong associations to cases that require prompt communication.
Efficient Learning of Restricted Boltzmann Machines Using Covariance Estimates

Learning RBMs using standard algorithms such as CD(k) involves gradient descent on the negative log-likelihood. One of the terms in the gradient, which involves expectation w.r.t. the model distribution, is intractable and is obtained through an MCMC estimate. In this work we show that the Hessian of the log-likelihood can be written in terms of covariances of hidden and visible units and hence, all elements of the Hessian can also be estimated using the same MCMC samples with small extra computational costs. Since inverting the Hessian may be computationally expensive, we propose an algorithm that uses inverse of the diagonal approximation of the Hessian, instead. This essentially results in parameter-specific adaptive learning rates for the gradient descent process and improves the efficiency of learning RBMs compared to the standard methods. Specifically we show that using the inverse of diagonal approximation of Hessian in the stochastic DC (difference of convex functions) program approach results in very efficient learning of RBMs.
Pelatihan pembuatan kuis online untuk perwakilan guru SD/MI pada badan kerjasama sekolah (BKS) Kabupaten Bantul

BKS Kabupaten Bantul is an organization that supervises all SD/MI Muhammadiyah/Aisyiyah in Kabupaten Bantul. The problem in BKS Kabupaten Bantul is most of the teachers are not fully utilizing technology to aid the learning process in their school especially when they held on a quiz. The teachers make a quiz and ask the students to write the answer and evaluate the answer manually one by one. The process takes a lot of time. Moreover, after evaluation the answer sheets will become unusable and piled up. Therefore, in this PPM program, we conduct a training to make an online quiz using Google Form and EasyTestMaker. Online quiz is easy to create and use, can be held anytime and accessed anywhere, has a timer and an automatic evaluation system, and the file is saved online. The method that used in this PPM program are preparation, introduction of online quiz, training, accompaniment, and evaluation. The result shows that most of the teachers can utilize technology to make an online quiz after training and eager to implement the online quiz in their school. We hope that this training can help teaching and learning activities in every school in the BKS Kabupaten Bantul.
Specific features of computer games localization process

The article describes the peculiarities of the localization process, during which the product changes in accordance with a particular culture or a market. Computer games localization is a part of game development, but it functions in its own environment. It has been stated that &#x0D; at present the overwhelming number of user interfaces of computer games are fully localized, yet with regard to the audio part, difficulties are observed. Glossaries should be used in the process &#x0D; of localizing sound parts. Files, formats and tools used by localization companies are considered. The conclusion is made about the complexity and versatility of the process of localization of com-puter games compared to the localization of other products
Generation of frequency-bin entangled two-photon state via cascaded second-order nonlinear processes

In this work, we propose and demonstrate the frequency-bin entangled two-photon state via cascaded second harmonic generation and spontaneous parametric down conversion (SHG-SPDC) processes in a single piece of PPLN waveguide. Our scheme is based on all fiber-pigtailed components at 1.5 μm telecom band. Two frequency-bins at 1531.34 nm and 1548.91 nm with bandwidth of 1.04 nm are prepared to be entangled. The frequency entanglement property of our generated two-photon states is measured by spatial two-photon quantum beating. A two-photon beating curve with a visibility of 87.92&plusmn;0.47% is obtained, showing a good property of frequency-bin entanglement.
On Domination and Control in Strategic Ability.

We propose a technique to compare partial strategies for agents and coalitions in multi-agent environments with imperfect information. The proposed relation mimics the game-theoretic notion of strategic dominance: a stronger partial strategy can replace a weaker one in a full strategy, while preserving the enforceability of a given goal. Our version of dominance is based on a new notion of input/output characteristics for partial strategies. Intuitively, the inputs are the states where the strategy gains control over execution, and the outputs are the states where it returns the control to the environment. Moreover, we identify the sources of dependence between partial strategies, and show conditions under which they can be analysed in a fully independent way. We evaluate our approach on two scalable benchmarks from the literature. The experiments are carried out for the tasks of incremental synthesis of uniform strategies and optimization of a winning strategy, with very promising results.
A Deep Single-Pass Learning for Optical Recognition of Handwritten Digits

We describe a new deep learning model - Deep Single-Pass Learning  (DSPL) that can learn a data set only a single pass for recognition and prediction  with high accuracy of the optical recognition of handwritten digits problem. DSPL  consists of several stacked convolutional layers to learn features automatically and  Extreme gradient boosting (XGBoost) is set the last layer for predicting the class  labels. The learning time is O ( Lc 2 mnpq ) + O ( x ( Kt + log B )), which is less than  the learning time of a deep learning - Convolutional Neural Networks (CNNs).  The network is no need for iteration to re-adjust the weight during the feature  learning process. The results of the experiments in the test set show that our  model handle the problem well and provides better accuracy than other models  i.e. CNNs, XGBoost, LR, ETC, GBC, RFC, GNB, and DTC, including MLP and  SVC families, with that DSPL provides 99.98% accuracy.
Kalimat Motivasi dalam Iklan Teknologi sebagai Bahan Ajar pada Pembelajaran Bahasa Indonesia di SMP kelas VIII

This study aims to: (1) find motivational sentences in technology advertisements in various sources, (2) describe idiomatic motivational sentences, (3) describe idiomatic motivational sentences utilization from technology advertisements in various sources can be used as teaching materials for Indonesian class VIII of Middle School. The method used in this research is descriptive qualitative. Data collection techniques in this study used the technique of listening and note taking by collecting data words or sentences that motivate and boast in advertising technology, as well as literature study techniques used to support this research. The results of this study are: (1) eight types of motives that serve as motivational sentence markers in technological advertising, including sophisticated motives, offer motives, trust motives, motives for overcoming problems, motives for meeting needs, motives for evidence, motives for supporting styles, and motives for healthy living , (2) six idiomatic motivational sentences in technology advertisements, (3) idiomatic motivational sentences from technology advertisements in various sources are used as teaching materials for Indonesian VIII grade junior high school, ad text learning related to Basic Competencies 3.3 Identifying advertisement text information, slogans, or posters (boast and motivate) from various sources that are read and heard.
Many-target, Many-sensor Ship Tracking and Classification

Government agencies such as DARPA wish to know the numbers, locations, tracks, and types of vessels moving through strategically important regions of the ocean. We implement a multiple hypothesis testing algorithm to simultaneously track dozens of ships with longitude and latitude data from many sensors, then use a combination of behavioral fingerprinting and deep learning techniques to classify each vessel by type. The number of targets is unknown a priori. We achieve both high track purity and high classification accuracy on several datasets.
Teaching the Hardware Implementation of Cybesecurity Encryption Algorithms on FPGA using Hands-on Projects

technologies for use in the field of hardware security to create a secure platform for an upcoming quantum era.
PEMBUATAN ALAT PENDETEKSI KEBISINGAN UNTUK BUDIDAYA BURUNG LOVE BIRD BERBASIS ARDUINO DAN ANDROID MELALUI WIFI

Created a tool to increase Love Bird production so that farmers do not have to worry about the condition of the Love Bird bird if there is noise that will disrupt the bird while laying eggs.This research was conducted by making a detection device to provide information on the status of noise intensity through Android.Thus it can prevent the Love Bird from being stressed when incubating its eggs, the effect is that if the Love Bird sires are disturbed by sound, they will lay eggs outside their cages "glodok", or they will not incubate their eggs.Therefore the breeders must protect the Love Bird from sudden noise.This tool will detect outdoor noise in the enclosure, the sound sensor uses an analog sound sensor v2. This sensor will send data to the Arduino microcontroller. Then the Arduino microcontroller will process the data according to the program that has been made. Data that has been processed by the Arduino microcontroller will turn on the incandescent lamp, turn on the dc fan, send information to the android that there has been noise, and move the servo motor to close the window, so that noise does not enter the cage and disturb the laying birds. And also this tool can detect if the drum room is too hot then the dc fan lights up, and if the drum temperature is too cold it will turn on the incandescent lamp as a heater. In the application the user can see decibels at this time, and can see the history on what date and what time the noise has occurred. Kata Kunci: Arduino uno R3, noise, analog sound sensor v2, DHT11 sensor
A versatile solution for long-term preservation of research data: Data Life-Cycle Management: the Swiss Way

Developed in the context of the 2017-2020 Swiss national programme Scientific information: Access, processing and safeguarding, the DLCM solution (dlcm.ch) consists of an open and modular architecture for long-term preservation of research data. While being compliant with the OAIS standard, the proposed solution makes the deposit of research data straightforward, yet allows the qualification of the submitted formats so as to inform users of the risks incurred on the long term.
Implementasi Jaringan CCTV Di Sekolah Tinggi Teknologi Pagar Alam

This study aims to implement CCTV networks using wireless at Pagar Alam College of Technology. The security system of CCTV installed using coaxial cable and is not integrated with Android. This study uses PPDIOO method in the form Prepare, Planning, Design, Implement, Operate and Optimize stages. The security system uses IP camera so it can be accessed wirelessly and PIR sensor that can detect presence living things. Servo can move to 180o expand monitoring range. When indicated the existence of living, the system will activate alarm and send SMS to User. The system testing method uses black box testing by testing the functions according to the user's needs using the Questionnaire. The results of this study are PIR sensor can detect movements within distance 5 meters, the duration of the alarm for 1 minute 6 seconds, the average delay sending notifications for 5 seconds, SMS delay time depends on network conditions that time.
Research Guides: Using Primo: The Library Discovery Search Tool: Home

Learn how to use the features of Primo, including how to SEARCH EVERYTHING - books, e-books, journal or newspaper articles, how to borrow print materials from the UFindNJ network of academic libraries, and how to access and manage your library account.
Optimization of Target Oriented Network Intelligence Collection for the Social Web by Using k-Beam Search

Shaha, Aditya Tripathy, B. K.Target Oriented Network Intelligence Collection (TONIC) is a problem which deals with acquiring maximum number of profiles in the online social network so as to maximize the information about a given target through these profiles. The acquired profiles, also known as leads in this paper, are expected to contain information which is relevant to the target profile. TONIC problem has been solved by modeling it as search problem and using heuristics to direct the best-first search on the social graph. The problem with this approach is that in case of dense neighbors of the target profile the computation of the heuristic can be significantly expensive. In this paper, we have introduced a k-beam search Heuristic which significantly mitigates this overhead.
Revisão por Pares na Aprendizagem de Modelagem de Sistemas: concepção de uma ferramenta de suporte

The adoption of collaborative learning techniques for software engineering education provides the opportunity for discussing software modeling issues considering multiple points of view. As a consequence, students are expected to develop better models for software problems. To do so, it is necessary to develop or adapt tools that support teachers and students when adopting this approach. This paper describes a study on the use of the Collaborative Learning Peer Review technique in a System Modeling courses. As a result, we have a set of requirements for a tool to support this technique for teaching modeling software with UML (Unified Modeling Language)
Design Of The Needs Of Educational Services In Gagas Ceria Kindergarten Using Integration Education Quality And Refined Kano

Abstract The importance of education for children of early age the more years the higher. It is also followeb by growth in the number of Kindergartens in many provinces in Indonesia, especially in West Java Province which has increased in recent years, with a ratio of more growth of private Kindergarten compared to domestic Kindergarten. It suggests that competition of private Kindergarten is more competitive compared with domestic Kindergarten, one of which is TK Gagas Ceria that is an object in this research. TK Gagas Ceria that has A accreditation, but in the last fre years the decreased in applicant from students who previously have taken early childhood education such as Play Group and Toodler in the Gagas Ceria Foundation. The presence of the problem of service Gagas Ceria Kindergarten to make the school need to identify the appropriate service for prospective customers. The study aims to improve the quality of educational services of TK Gagas Ceria using the integration of Education Quality and Refined Kano to identify 21 attributes of the services needs of education needs of TK Gagas Ceria. Based on the results of Education Quality and Refined Kano, there 11 atributes needs to prioritize. The recommendations are formulated based on the results of data processing and analysis involve TK Gagas Ceria sides. These recommendations contain the attributes of services requirements that need to be prioritize as the True Customer Needs. Keywords: Kidergarten,Neeed Analysis, Education Quality, Refined Kano