Reviewerly/exHarmony huggingface dataset:
Aplikasi Game Edukasi Tebak Gambar Dan Menyusun Kata Untuk Siswa TK Berbasis Android

In the world of education, learning about arranging words and numbers is actually taught when children enter kindergarten.The material presented at Kindergarten Pertiwi 1 Blangu still uses the usual learning method that relies on wooden blocks as an introduction to be considered inadequate to create interest. student learning goes up. The learning ability of kindergarten students is very varied, some are dexterous in remembering every word and number, some are weak learning how to pronounce words and numbers due to the lack of interesting learning media for students. The purpose of this research is to make educational games about arranging words and numbers. Data collection was carried out at Kindergarten Pertiwi 1 and met with kindergarten teaching staff for interviews and observations. Making image assets in this study using Corel Draw 12 and Adobe Photoshop CS6 software. This educational game is made using Construct 2, then the results of the master file are exported into an apk bundle file. This word and number recognition educational game application has 2 features, a material menu containing 3 sub menus, and a hint menu containing instructions on how to use this game. Testing on the Blackbox shows all the features contained in this software can run as expected since the beginning of development and manufacture. The SUS test that has been carried out has obtained 83 results with the following conditions: a.) The level of user acceptance is in the acceptable category, b.) The grade level of the scale is in category B, and c.) The rating adjective is in the excellent category.Keywords: Android, Construct 2, Game edukasi, TK Pertiwi 1 Blangu.
Aplikasi Location Based Service (LBS) Objek Wisata Tanggamus Berbasis Android

AbstractThe presence of smartphones with various existing applications has an impact on the lives of the surrounding community. Various applications are present and always growing in this tourism sector. One of them is as a digital introduction media for destinations in Tanggamus Regency which contains information needed by tourists, facilities, rides offered and other supporting facilities such as gas stations, ATMs, police stations, workshops and so on. Tanggamus Regency is a district located in Lampung Province which has several natural tourist sites that are worth visiting, but there are still many people who are not very familiar with the existing destinations. This occurs due to the lack of exposure and lack of introduction to the wider community in various regions. In addition, there is no android-based application system that serves to introduce and convey information on tourist destinations to the wider community and there is no special digital media that promotes Tanggamus tourism. One solution to solve the problems that arise is to build a Location Based Service (LBS) application as a geographic information system (GIS) point with an Android-based user interface. The results of the LBS application for tourist destinations in Tanggamus Regency are in the form of an information system that is able to provide details of tourist locations and can introduce tourism locations in Tanggamus Regency more widely so that it makes it easier for the public to know and can become a technology-based marketing or introduction media and tourists who want to take a vacation no longer need to search for information via google with lots of keywords.
LibGuides: Federal Register Library: Help Resources

The Federal Register is the official journal of the federal government of the United States. The database is updated daily and its coverage is comprehensive, beginning from inception in 1936.
High School Students’ Problems in Speaking

The aims of this research were to describing the students’ problem in speaking and finding out the factors that influence students’ eleventh grade in speaking. This researcher used qualitative method. The population of this research was the eleventh grade of SMAN 1 Palopo in academic year 2018/2019.The sample of this research consist of students MIA 1, MIA 2, MIA 3. The researcher took five samples from each class. The researcher used the students score from spoken test to categorize as samples of this research. The instruments of this research were questionnaire, oral speaking test and interview. The results showed that the students problem in speaking such as accuracy, pronunciation, vocabulary, grammar, and fluency. Meanwhile from the result of interview there were several factors that influenced students’ speaking performance namely performance condition, affective factors, listening ability and topical knowledge.
LibGuides: Evaluating and Selecting Resources: About

Use this guide to learn how to evaluate different types of resources and determine their value.
Research Replication Prediction Using Weakly Supervised Learning

Knowing whether a published research result can be replicated or not is important. Carrying out direct replication of published research incurs high cost. It is therefore desirable to have a machine learning aided automatic prediction of a result's replicability. Such predictions can provide a confidence score for each article which can further provide guidelines for spot-checks.Since we will only have access to a small size of annotated dataset to train a machine predictor, we explore the possibility of using weakly supervised learning approaches to improve the prediction accuracy of research replication using both labelled and unlabelled datasets based on text information of research papers. Our experiments over real-world datasets show that much better prediction performance can be obtained compared to the supervised models utilizing only a small size of labelled dataset.
Faculty of Science Education and Teacher Traning Sunan Kalijaga State Islamic University

This development research aims to: (1) produce the learning medium of Augmented Reality (AR) on natural science subject on subject water recycle in class V MI Wahid Hasyim; (2) knowing the quality of the products the learning medium of Augmented Reality (AR) on natural science subject on the subject matter of water recycle ; (3) find out the results of the response of teachers and students so that decent media used in learning natural science. The development model used in this medium is the modified Thiagarajan 4D model. The stages carried out consist of three stages, namely Define (defining), Design (design), and Develop (development). The media for learning Augmented Reality (AR) was assessed by 1 media expert, 1 matter expert, 1 peer reviewer, 1 class V teacher, and 10 V grade students MI Wahid Hasyim to find out student responses. The instruments used were questionnaires and evaluation sheets using non-objective description forms for testing the quality of science learning media products. The results of the study are: (1) Augmented Reality (AR) media learning products have been developed for water cycle matter run on Android version 4.1 jelly bean, (2) Learning media for Augmented Reality (AR) water cycle matter with feasibility according to the overall assessment of reviewers and peers reviewers obtain very good quality ie 90.2%, (3) response or response of class V teachers is very good with a percentage of 82.57%. Likewise, the students' responses obtained a percentage of 90.2% with a positive response so that the learning media had a quality category on the Very Good criteria which was also supported by the results of students who experienced an increase of 35.8%. Based on the results of data acquisition shows that the learning
Removing Dimensional Restrictions on Complex/Hyper-complex Convolutions

It has been shown that the core reasons that complex and hypercomplex valued neural networks offer improvements over their real-valued counterparts is the fact that aspects of their algebra forces treating multi-dimensional data as a single entity (forced local relationship encoding) with an added benefit of reducing parameter count via weight sharing. However, both are constrained to a set number of dimensions, two for complex and four for quaternions. These observations motivate us to introduce novel vector map convolutions which capture both of these properties provided by complex/hypercomplex convolutions, while dropping the unnatural dimensionality constraints their algebra imposes. This is achieved by introducing a system that mimics the unique linear combination of input dimensions via the Hamilton product using a permutation function, as well as batch normalization and weight initialization for the system. We perform three experiments using three different network architectures to show that these novel vector map convolutions seem to capture all the benefits of complex and hyper-complex networks, such as their ability to capture internal latent relations, while avoiding the dimensionality restriction.
CAPT and its Effect on English Language Pronunciation Enhancement: Evidence from Bilinguals and Monolinguals

Nowadays there are several challenges for English teachers as well as researchers regarding how to teach foreign language pronunciation more effectively. The current study aimed to explore the effect of computer-assisted pronunciation teaching (CAPT) on Persian monolinguals and Turkmen- Persian and also Baloch- Persian bilinguals’ pronunciation considering production and perception. A sample of 48 female mono and bilingual 7th-grade students participated in this study and made the experimental and comparison groups. All the participants took the Oxford Placement Test and accordingly were in the beginner level of English language proficiency (95.83% of the participants’ scores ranged from 0 to 15). The experimental group experienced a technology-based instruction while the comparison group benefited from traditional listen and repeat method of pronunciation teaching. Two Two-way between-group ANOVAs were used to define the influence of CAPT on pronunciation production and perception of the mono and bilingual participants. The results of the study indicated that CAPT had a significant effect on pronunciation production while pronunciation perception was comparatively more enhanced through the traditional method. Regarding mono and bilingualism, it was also found that bilinguals significantly outperformed monolinguals in pronunciation production in both groups while there was no significant difference between them in pronunciation perception. There were also no interaction effects for pronunciation perception or production scores. The results generally showed that CAPT can be beneficial specifically when it is used along with traditional methods at schools in beginner levels.
This is the first article in the test

Through the cooperation of many people and registering accounts with different identities, the whole process and all-round test of the contribution system can be carried out, including but not limited to the use of the author's identity for contribution, the use of publishing editor's identity for contribution process service, the use of journal editor's identity for manuscript, column editor's identity for manuscript review, and the use of editor's identity for arrangement and proofreading Editing, typesetting and proofreading of manuscripts.
Bayesian modelling of complex dependence structures

Complex dependence structures characterising modern data are routinely encountered in a large variety of research fields. Medicine, biology, psychology and social sciences are enriched by intricate architectures such as networks, tensors and more generally high-dimensional dependent data. Rich dependence structures stimulate challenging research questions and open wide methodological avenues in different areas of statistical research, providing an exciting atmosphere to develop innovative tools. A primary interest in statistical modelling of complex data is on adequately extracting information to conduct meaningful inference, providing reliable results in terms of uncertainty quantification and generalisability into future samples. These aims require ad-hoc statistical methodologies to appropriately characterize the dependence structures defining complex data as such, further improving the understanding of the mechanisms underlying the observed configurations. The focus of the thesis is on Bayesian modelling of complex dependence structures via latent variable constructs. This strategy characterises the dependence structure in an unobservable latent space, specifying the observed quantities as conditionally independent given a set of latent attributes, facilitating tractable posterior inference and an eloquent interpretation. The thesis is organized into three main parts, illustrating case studies from different fields of application and focused on studying modern challenges in neuroscience, psychology and criminal justice. Bayesian modelling of the complex data arising in these domains via latent features effectively provides valuable insights on different aspects of such structures, addressing the questions of interest and contributing to the scientific understanding.
Effektivitetsanalys av Vakuumsystemet i Pappersmaskin 1 : En del av energikartläggningen på Nymölla Bruk

Nymolla Mill is a papermill in the paper division of Stora Enso. Due to its size, the company is forced by law to make energy mappings every fourth year, in order to ensure that that the company is ...
Tafsir Ekologis Al-Qur’an Surah Al-Mu‘minun Ayat 18

The problem of water quality and quantity is getting more of a concern from time to time. Water crisis, flooding, land subsidence, intrusion and rising sea levels are serious threats facing modern society today. The de-constructive behavior and exploitation of water resources on a large scale and irregular natural management make the ecosystem on earth unbalanced and in the end lead to disaster. The writing is a literature research using the Thematic Method (al-dirasah al-mawdu ’ iyyah), with an ecological interpretation approach. From the results of this study it was found that QS. Al-Mu'minun / 23: 18 requires an understanding of water resources based on positive and constructive culture towards the earth ’ s water reservoir.
Automated real-time disturbance report using categorized Phasor Measurement Unit (PMU) event data

Any uncertainty around a disturbance in the power system can be problematic for the operator when making decisions on how to proceed with the restoration process. Capturing the sequence of these disturbances, their uncertainties and how they affect the system state is improved by the use of Phasor Measurement Units (PMUs). These units provide synchronized measurements at the sampling rate of 50 Hz in the Icelandic power grid and are able to catch important characteristics of the disturbances. This thesis aims to find a procedure and a solution to classify these characteristics and to provide the operator with a detailed visual report in real-time of key parameters such as active- and reactive power, voltage and frequency, to explain the events and assist in further decision making. The thesis introduces the problem of classification for multivariate time series. To solve the problem, a convolutional neural network (CNN) was applied to the dataset. The networks outputs were then used to automatically generate detailed information and visuals for the assistance of the operators. The dataset consisted of 30 labeled events from the Icelandic power system,each containing 51 multivariate time series from the PMUs. The labels were four in total and consisted of a component trip, loss-of-load, islanding and oscillations events. The classification accuracy reached upwards 94.7% and run-time results showed a great success of keeping it in real-time, for an event of 30 seconds, the report was able to be classified and visualized in under 10 seconds after the event. The results also presented the possible need for additional data to further improve the deep learning model and introduce opportunities for further research and future enhancements both to implementation and to a more detailed visual automatic report.; Oll ovissa i tengslum við truflanir i raforkukerfinu geta valdið vandamalum fyrir stjornstoð þegar akvarðanir við stýringu og uppbyggingu kerfisins eru teknar. Að atta sig a atburðaras og sja hvernig þaer hafa ahrif a kerfið hefur farið miklum framforum með innleiðingu fasamaelitaekjum (PMU). Fasamaeligognin sem fengin eru i islenska flutningskerfinu hafa upplausn upp a 50 Hz og na að gripa mikilvaeg einkenni truflanna. Ritgerð þessi vinnur að þvi að finna ferli og lausn við flokkun a tilheyrandi eiginleikum, og að veita stjornstoð itarlega myndraena skýrslu i rauntima þar sem fram koma helstu atriði varðandi afl, spennu og tiðni, til þess að aðstoða við að svara spurningunni hvað gerðist? og til að hjalpa við aframhaldandi akvarðanir. Tekið er fyrir verkefnið um flokkun fjoldabreytutimagagna. Fyrir lausn vandamalsins var notast við gerð djuptauganets sem kallast þyrpinganet (CNN). Utkoman ur spa netsins var siðar notuð til uppbyggingar itarlegrar skýrslu sem aðstoðar stjornstoð baeði myndraent og með tolulegum upplýsingum, að skilja atburðinn betur. Gognin samanstoðu af 30 merktum atburðum ur islenska raforkukerfinu, þar sem hver atburður innihelt 51 fjoldabreytutimagogn fra fasamaelitaekjunum. Flokkunin var ferns konar,…
Teacher's Strategies in Improving the Autonomous Learners in Learning English

This research is aimed to find out the strategies done by the teachers in improving their learner autonomy in learning English and to describe how the teachers implement the strategies in teaching-learning process. The researcher is conducted research at Mts Muhammadiyah 1 Banjarmasin because the researcher realized that the student's autonomy at the school still lacked in learning English.The type of this research is descriptive qualitative research. The subject of this research are two English teachers, and the object of this research are the teacher's strategies in improving the autonomous learners in learning English. In conducting the research, to collect the data the researcher did observation, interviewed the English teachers and used the teacher's lesson plans for documentary. The collected data were analyzed using descriptive qualitative analysis method.The result of this research show that there are some strategies done by the teachers in increasing their students' autonomy in learning English, namely; study group, answer the questions on the blackboard, tasks, and persuasive communication. But, in this research the researcher also found that there are some strategies above can't apply by the teachers in this phase (during corona pandemic), so the researcher divided the result into two phases. The first phase is before the corona pandemic, the researcher found that the teachers use and apply all of the strategies above. The second phase is during corona pandemic, in this phase the teachers only can apply two strategies, there are; tasks and persuasive communication.
Recognition of Driver Braking Intensity of EHB System Using a Hybrid Learning Approach.

Accurate recognition of driver braking intensity is of great importance for intelligent braking system. In this paper, the braking intensity is classified into four clusters based on an unsupervised Gaussian mixture model (GMM). Then, the architecture of an adaptive-network-based fuzzy inference system (ANFIS) is proposed for braking intensity prediction. A batch learning rule that combines the recursive least squares and gradient descent method used for training ANFIS is adopted to improve the generalization capability. The training data are collected from a hybrid vehicle under real driving conditions. In addition, co-simulation with the software of MATLAB/Simulink and Hardware-in-the-Loop (HiL) tests for an Electronic-Hydraulic Brake (EHB) system are carried out. In comparison to other typical learning methods, the simulation and experimental results demonstrate the effectiveness and accuracy of the proposed hybrid learning approach for braking intensity recognition in different braking scenarios.
Find your login details and log in to your Monsido account

Our website is regularly checked for quality assurance by Monsido. This system checks our website for common content issues including: spelling mistakes, broken links, accessibility issues and more.
Comparative Study of Opinion Mining and Sentiment Analysis: Algorithms and Applications

The massive amount of data available online increases the ability to analyze and understand how people are thinking. The internet revolution has added billions of customer’s review data in its depots. This has given an interest in sentiment analysis and opinion mining in the recent years. People have to depend on machines to classify and process the data as there are terabytes of review data in stock of a single product. So that prediction customer sentiments is very important to analyze the reviews as it not only helps in increasing profits but also goes a long way in improving and bringing out better products.  In this paper, we present a survey regarding the presently available techniques and applications that appear in the field of opinion mining, such as: economy, security, marketing, spam detection, decision making, and elections expectation. The survey is based on the techniques used with English-written data however it is important for future studies on other languages like Arabic and Malay.
NAGGING FOOD INSECURITY AMIDST PUBLIC POLICIES, STRATEGIES, PROGRAMMES AND PROJECTS IN NIGERIA: THE MISSING LINKS

Nigeria has had five decades (1970-2019) of numerous public policies, strategies, programmes and projectsaimed at boosting agricultural production for the attainment of food security. But, the outcome is that seven outof ten Nigerians are food insecure. The study set out to establish the missing links. Theoretical and documentaryresearch methods were used to identify the missing links, which were subjected to factor analysis to ascertainthe significant ones. A survey research design was adopted to get four hundred (400) purposively selectedacademics and practitioners in food production to authenticate the significant missing links. Respondents’ onlinevisibility guided their selection as people in the best position to respond to questions on Nigeria’s agriculturalproduction and food security. Each of them was engaged in virtual interaction through internet and social mediaplatforms to obtain information as guided by a questionnaire covering questions on the ascertained significantmissing links and their relationship with science technology and innovation (STI)with answer options in likertscale.Scores were analysed by comparing calculated values with decision values to confirm affirmation andotherwise. Results showed six (6)authenticated significant missing links: predominance of smallholdersubsistence farming, use of rudimentary tools, unimproved varieties of seeds and other inputs, traditional storageand preservation practices, deficit of marketing infrastructure, and dependence on rain-fed agriculture. All ofthese were related to STI, attributable to poor STI adoption, and can be solved by STI adoption, which can aswell address the four dimensions of food security. The study recommended STI adoption for agriculturalproduction to attain food security status in Nigeria.