Reviewerly/exHarmony huggingface dataset:
Analyzing Error Pronunciation in Spelling Words

Pronunciation in daily communication has the main role. Pronunciation is studied by repeating word sounds and correcting them. Some students are ignorant of pronunciation’s function.  This research was desiderated to analyze error pronunciation in spelling words by three classes of MA Plus Al-Mashduqiah students (10th grade-12th grade) Patokan. The error pronunciation occurred as the usual sense in pronouncing the words that not only happen in 10th grade but also in 11th and 12th grade. In order to get data, the participants were given word lists that contained several words and then ordered to pronounce them one by one. These words chose to suspect the common mistakes pronounced by participants. For instance, the word ‘flood’ is pronounced the same as the word ‘door’, the word ‘examine’ is pronounced the same as ‘mine’. Then, an in-depth investigation was used to find out the learners’ consideration pronouncing the words. The result discovered that the learners tended to pronounce the words that referred to other words that contained the same orthography. Using cross-section design, this research randomly selected 60 students. This research found that there were significant gradations among the groups. The amount of error pronunciation was in line with the level of those three groups. The highest error found in 10th grade as new students in that school.
Divisor Class Halving Algorithms for Genus Three Hyperelliptic Curves

In an (hyper)elliptic curve cryptosystem, the most important operation or the most time-consuming operation is the divisor scalar multiplication which consists of a sequence of doubling (of divisor) and addition (of two divisors). Point halving algorithms for elliptic curve cryptosystem and divisor halving algorithms for genus-2 hyperelliptic curve cryptosystem had been successively put forward to take the place of doubling algorithms for speeding up (hyper)elliptic curve cryptosystem. We present an outline for an algorithm for divisor halving on genus-3 hyperelliptic curves over the binary field and give some explicit formulae for a class of genus-3 curves. Our algorithm improves previously known best doubling algorithms in most cases. A halve-and-add binary method for divisor scalar multiplications is presented.
Parents, Teachers and Students Level of Awareness on the Implementation of Disciplinary Actions on Bullying at Mayamot National High School: Basis for Localized Policy Guidelines on Child Protection

This descriptive action research study aims to determine the level of awareness of parents, teachers and students on the implementation of disciplinary actions on bullying of Mayamot National High School during school year 2015-2016. The salient findings of the study are as follows: (1) Parent, teacher and student respondents have the same level of awareness on the implementation of disciplinary actions on bullying in terms of knowledge, process and effectiveness as evidenced by overall weighted means of 2.97, 3.18 and 2.96 respectively all verbally interpreted as Aware. This implies that the parent, teacher and student respondents were knowledgeable about the implemented disciplinary actions on bullying. Also, they all believed that the process of disciplinary actions on bullying was well implemented and effective in their school; and (2) There is no significant difference between the level of awareness of the parents, teachers and students in the implementation of disciplinary actions on bullying as evidenced by the computed F-ratio of 1.56 is less than the tabular value of 3.35 at 0.05 level of significance.           Based from the findings and conclusions, the following are recommended: (1) School heads may promote whole-school approaches to ensure that there is an open-communication and clear understanding of issues related on the implementation of disciplinary actions on bullying in the school community through launching “Anti-Bullying Week” each year to review and evaluate the effectiveness of intervention programs implemented by the school pursuant to the provision of Sec 7 of Republic Act No.10627, otherwise known as Anti-Bullying Act of 2013; and (2) The parents and community must collaborate in the process of creating a bully free school community effectively.
Clustering Data in Power Management System Using k-Means Clustering Algorithm

Electricity is a source of current that cannot be released from life because it is needed as a means of production and helps solve problems in daily life. Most users use electricity without realizing the amount of electricity used in that period, it can make electricity usage soar because there is no control of electricity usage. The problem of the amount of electricity usage also occurs in campus buildings, logistics staff cannot control the use of electricity because there is no history of electricity usage in certain buildings. To solve this problem, an IOT-based KWH electricity usage monitoring system was built. Furthermore, this application has a data clustering calculation using the K-Means algorithm which aims to classify campus area data according to its electricity usage whether it enters areas that use large, normal or low loads. By using information from the data clustering, logistics employees can make a policy to make electricity savings. This system has three main parts, namely the hardware system, IoT server, and website monitoring application. In this research focuses on making website monitoring and clustering data applications. From the results of tests conducted by the K-Means algorithm has the highest accuracy value of 83.3%.
Occlusion Deep Alignment Network

The performance of face localization system often degenerates when occlusions occur. In this paper, we propose Occlusion Deep Alignment Network(ODAN), which is robust to occlusion. Occlusion detection and rough face alignment are employed simultaneously, where the occlusion detection of landmarks is treated as a regression problem. Based on occlusion information, localization offset scaling is employed to transform the difference between the groundtruth and the rough landmark estimation to another linear space to generate target positions for precise face alignment, reducing the difficulty of the regression task. Finally, the outputs of the proposed model are transformed back to Euclidean Space. Experiments on two public datasets show that the proposed method achieves state-of-art performance under severe occlusion both in accuracy and efficiency.
Multimedia Development of English Learning for Recount Text

In this study aims to: (1) produce English learning multimedia products for recount text material, (2) find out the feasibility of English learning multimedia products for recount text material, and (3) find out the effectiveness of English learning multimedia multimedia products for recount text material for class VIII students at SMPNJ. This research method is a research and development (RD (2) the product developed is suitable for use as a complementary medium for learning English for recount text learning; (3) an increase in the average score of all students from the pretest and posttest results of 0.90 (N-gain ≥ 0.7) . This means that the effectiveness of the product being developed is in the high category
Physical Thorax Model and 2D Grid of Force Sensors to Monitor Respiration

Abstract Sleep disorders impair the quality of life for many individuals, but often go undiagnosed and untreated due to the cost and sleep-disturbing aggravation of polysomnography, the clinical sleep test. Simpler sleep monitoring systems that could be used at home may provide useful health information. A 2D grid of force sensors within a mat beneath the thorax of a sleeping subject has been reported to enable monitoring of respiration during sleep. A physical model of a thorax over such a 2D grid of force sensors may enable more tests and perturbations of parameters than could be done using only human subjects. The purpose of this project was to develop and test a physical model of a thorax undergoing volume changes, and measuring the changes in force by a grid of force sensors under the model. A prototype system was developed. Early testing shows promise for being able to monitor the changes in force as volume of the model changes. More development and testing are required toward development of improved algorithms and systems for sleep monitoring mats.
Optimized Layout of the Soil Moisture Sensor in Tea Plantations Based on Improved Dijkstra Algorithm

Based on the clustering center of data, this paper optimizes the data transmission path, and proposes an improved Dijkstra algorithm, which is applied to the path optimization of soil moisture sensors in tea plantations. Firstly, the date of soil moisture in tea plantation is collected under the condition of full coverage of the sensor network. Then, the AP clustering algorithm is used to cluster collected data to obtain the cluster center. Secondly, the dissimilarity values of the soil moisture data and the weighted combination of distance between the sensor nodes are used to identify the edge weights and calculate the adjacency matrix of the Dijkstra algorithm. Finally, with the clustering center as the starting point and the convergence point of wireless sensor network as the end point, Dijkstra algorithm is used to search the path. In order to verify the superiority of the proposed algorithm, the algorithm is compared with the ant colony optimization algorithm. In this paper, the data dissimilarity on the path is 25.0652, the total cost of the path is 0.3613, and the difference between the average soil moisture of the tea plantation is 0.1872 and the number of sensors required is 6, The ant colony algorithm obtained the data dissimilarity on the path of 20.4538, the total cost of the path is 0.5483, and the difference between the average soil moisture of the tea plantation is 0.7321 and the number of sensors required is 9. The test results show that the date of path obtained by this method has the largest dissimilarity and the shortest path, and the data collected by this method is representative, which can accurately reflect the distribution of soil moisture in tea plantations. At the same time, the number of sensors is reduced from 25 to 6, reducing the cost of the system.
Digital Wellbeing Educators – A compendium of best practices

We live in a highly digitally connected Europe where people of all ages use the internet to connect, communicate, explore and learn through digital media, however a recent JISC study reported that educators in Higher Education institutions are concerned about the wellbeing of their students in digital settings. In addition, the Opening Up education report shows that 70% educators in the EU understand the importance of digital literacy but only 20-25% students are taught by digitally confident educators. Improving the digital literacy of educators is required particularly in the area of digital wellbeing. Higher Education institutions are becoming increasingly aware of the consequences of digital overload on mental health of individual students, the societal impacts on relationships such as cyberbullying, technical issues such as cybersecurity and the addictive design of technology, fake news and the controversies surrounding radicalisation and challenges to democracy. The Digital Wellbeing Educators Project (funded by ERASMUS+ programme of the European Union) aims to increase the capacity of educators in Higher Education institutions to integrate digital education to promote the wellbeing of their students. The first step towards this has been to publish a Compendium of good practices that collects a number of materials showing how the challenges of the digital era are addressed by others so teachers are inspired and find solutions that can be transferred to their students. During the presentation we want to show the main points of this compendium and present the next steps that the project has prepared, which includes the development of an app and teacher’s digital pedagogy toolkit to support educators in developing their own digital competences and making their teaching more digital.
Linear Optimal Filter for Stochastic Uncertain systems with Multi-loss Packets and Finite-step Delays

This paper studies the linear optimal filter for networked control systems owning non-stationary observations noise. Taking phenomena of multi-loss packets and finite-step delay and uncertain parameters of the networked control systems into consideration, the model of multi-loss packets and finite-step delays are represented by a set of Bernoulli stochastic variables. The parameters uncertainties are depicted by multiplying the white noise sequence. In order to facilitate the derivation of the optimal linear filter, we first perform model transformation. Then the linear optimal filter with linear minimum variance meaning is developed via the projection theory and the innovation analysis technique. A numerical simulation illustrates that the algorithm is effective.
An Improved Local Dynamic Path Planning Algorithm for Autonomous Driving

In this paper, an improved autonomous driving local dynamic path planning algorithm is proposed. Based on the predefined road center points, a set of path control points is constructed, and a one-dimensional cubic equation is used to fit the path and construct a center line. A new curved coordinate system is provided using the center line, and the path candidates are generated by arc length and lateral offset. The overall path is selected in consideration of the total cost of path safety and comfort. The results showed that under different scenarios, the proposed local path planning algorithm can plan an optimal path that does not collide with static obstacles, and can ensure the comfort of autonomous driving vehicles and the real-time path planning.
ChronoModel version 2.0

The ChronoModel Application is intended to provide tools for constructing chronologies in archaeology in combining Events, Phases and temporal constraints.Models can be developed including data from any dating methods (14C, TL/OSL, AM, typo-chronology, …) and from archaeological and environmental contexts (stratigraphy, ordering between phases, duration or hiatus constraints).A user-friendly interface is proposed for entering the data, MCMC calculations can be inspected in details, models and results are presented using the Bayesian statistical framework.ChronoModel is a free and open-source cross-platform software (Mac, Windows, Linux). The current version 1.5 works with different calibration curves for 14C and Archaeomagnetism.
An Auxiliary Scheme for Automatic Marking of Chinese Reading Comprehension

The traditional manual marking has problems such as high time consuming and tedious process, especially for the review of subjective questions such as reading comprehension. Fortunately, the rapid development of information technology brings us many new concepts such as deep learning, machine learning and educational big data, which are profoundly changing the traditional teaching methods and further promoting the development of education developing towards the direction of modernization, informatization and intelligence. So, this paper proposes an auxiliary scheme for automatic scoring of Chinese reading comprehension for reducing unnecessary costs in the education process. Our scheme utilizes an improved LSTM neural network for keyword extraction and adopts word embedding for semantic information extraction. Firstly, we segment Chinese words and divide the text content into meaningful word strings. Then, the neural network is used to obtain keywords of the solution and a student's answer corresponding to the question. Finally, we exert the cw2vec word embedding method to capture the semantic information and calculate the semantic similarity between these keywords. Therefore, our method can assist the automatic scoring process. We verify the effectiveness of our method with comparing experiments.
EXPERIMENTAL STUDY ON CLOUD SECURITY FOR PERSONAL HEALTH RECORDS OVER PATIENT CENTRIC DATA

Cloud computing offers many services among one is Storage as a service.Using this service user can outsource his data and whenever required he can download or he can share with others.Using cloud computing PHR owner can share his documents, but due to security challenges in cloud computing the health records of owner must be encrypted before outsourcing.In order to provide security for owner health records ABE (attribute-based encryption) is best suitable for other encryption techniques.Using ABE the PHR owner can define access control over his encrypted cloud data.But using ABE dynamic polices over encrypted cloud data is big challenge.In this paper for achieving grant and revoke privileges over encrypted data Timestamp server is introduced.
A Novel Active Learning Algorithm for Robust Image Classification

Training samples need to be labeled before being used to train classification model, which usually takes too much labor and material resources. Recently, this problem has attracted widespread attention. In order to reduce the workload of labeling samples, we propose a novel active learning methodology, which uses locally linear reconstruction coefficients to construct semi-supervised data manifold adaptive kernel space. Comparing the new method with other sampling approaches on several real-world image datasets, experimental results indicate that the novel algorithm has preferable classification ability. Especially, it can show higher classification accuracy under the condition that only a few samples are selected to train the classifier model.
TATHWÎR ADAWÂT IKHTIBÂR MAHÂRAH AL-QIRÂAH BI ISTI’MÂL KAHOOT! FÎ AL-MADRASAH AL-TSÂNAWIYAH AL-HUKÛMIYAH BI SUMATRA AL-GHARBIYAH

This aimed to make or produce reading skills test tool using Kahoot platform. This was a research and model using the 4D model (defines, designs, develops, determinates), yet this was only up to the developing stage. The result of the development in this is that the researcher developed the reading skills test questions using the Kahoot platform. These questions are written on the platform, then a picture is inserted in the question, as well as the answer choices and the correct answer. The picture helps students to understand the commands of the questions and the researcher used one type of question, the quiz, which is a question by providing answer choices from A to D. The answer choices in this problem are in the form of triangles, squares, circles and squares that have been rotated.  The students used the smart phone.  In this online test, the educator determined the time to answer the question.
PENGEMBANGAN APLIKASI DELIVERY ORDER DI TAIWAN TEA HOUSE CSB MALL BERBASIS ANDROID

AbstractDelivery order is an activity and provision of services where consumers order products supplied by producers and usually use a medium of communication by telephone or internet and the products ordered will be delivered to the consumers without consumers need to come and meet directly with the seller / producer.Android is a Linux-based operating system designed for touch screen mobile devices such as smart phones and tablet computers. Android was originally developed by Android, Inc., with financial support from Google, which then bought it in 2005. The operating system was released officially in 2007, in conjunction with the establishment of the Open Handset Alliance, a consortium of companies hardware, software, and telecommunications that promotes open standards mobile devices. The first Android phone went on sale in October 2008.Android-based delivery application order that currently used by Taiwan Tea House CSB Mall doesn’t have external database yet, which cost many problems. Development of this Android-based delivery order application at Taiwan Tea House CSB Mall that will be the end result of this essay is expected to solve those problems.Keywords : delivery order, Android, Linux, development, external database.
Internet of Things as a mean to motivate freshmen students in the “Facultad de Informática” of the National University of La Plata (UNLP)

This article describes the process of including a series of IoT workshops during the years 2017, 2018 and 2019 in the subject “Seminario de Lenguajes opcion C” of the Facultad de Informatica (Computer Science Faculty) of the UNLP (National University of La Plata). The goal of these workshops were to motivate students in the learning process showing that the C programming language is still current with new technologies. The workshops needed appropiate devices and trained teachers. In the year 2017 Zolertia Z1 devices were used, in 2018 the workshops switched to Arduino Nano boards and finally Duinobot V1.2 boards were used in 2019. The students learnt about hardware, communications and application development. In the year 2017 and 2018 the participant students showed better performance than the ones that did not participate, in 2019 a poll was included. The activity was motivating to students and a contribution to their training. These experiences will determine if IoT can be included as a topic in the subject and through the development of simple specific applications.
Study on the Method of Extracting Diabetes History from Unstructured Chinese Electronic Medical Record

In this paper, based on the real electronic medical record data of the hospital, a customized method of rule-based learning and information extraction is designed, and three steps are adopted to realize the extraction of Chinese information: sampling and labeling. The medical history information of 600 electronic medical records (including current medical history, past history, personal history, family history, etc.) were randomly selected, and the information needed to be extracted (taking diabetes history as an example) was marked by the labeling platform developed in this study. According to the annotation results, the extraction template is summarized, and the extraction template can be directly used to extract the regular expression extraction rules, and these rules can be used to extract the actual information. The method of manual verification and automatic verification is used to verify the effectiveness of the method. By using the method of natural language processing and rule-based information extraction, an algorithm for extracting customized information from unstructured Chinese electronic medical record text data is designed and implemented. Aiming at the extraction of diabetes history in the hospital, the field verification of a single department has achieved good results.