Reviewerly/exHarmony huggingface dataset:
A Study of the Construction of English Hidden Curriculums at Primary Schools in China

The hidden curriculum is an important part of curriculums, and constructing the primary school English hidden curriculum is helpful for the implementation of the new National English Curriculums, the development of students&amp;rsquo; key competencies and the reform of basic English teaching in China. However, according to the survey conducted with 40 primary school leaders, 60 primary school English teachers as well as 300 primary school students, the hidden curriculum is always ignored in primary school English teaching in China. Schools should meticulously design the educational environment on campus, highlighting the characteristics of English hidden curriculums, integrate English into the class culture, optimizing English educational environment. It is necessary to build a harmonious relationship between teachers and students, to enhance students&amp;rsquo; motivation of learning English, to mobilize social and family participation, and to build multiple hidden curricular resources of English so as to promote the reform of English teaching and improve the quality of English teaching at primary schools in China.
Soil Temperature Prediction under Limited Data Condition

Soil temperature plays a key role in crop water requirement and crop yield.The accurate field estimation of soil temperature is difficult and expensive.Therefore the present study focuses on the estimation of soil temperature in Mohanpur using Artificial Neural Network with input weather data such as maximum temperature, minimum temperature, wind speed, sunshine hours and the results shows that a good correlation exists between the maximum and minimum temperature with the soil temperature.The results statistics shows that with all the given input data condition model shows good results (R 2 = 0.95, RMSE = 1.54,MAE = 1.21) and also the model behaves well for sparse data condition i.e.only when maximum and minimum temperatures are available results (R 2 = 0.91, RMSE = 1.86,MAE = 1.46). K e y w o r d sSoil temperature, Data condition, Crop
Meta-cognitive Strategies in College Students’ WeChat Mobile EnglishLearning

The development of the Internet information technology and the popularization of mobile devices have brought about a new paradigm of learning, Mobile Learning, which is becoming increasingly common in the college English learning.In addition, as a multifunctional messaging and social media application attached to mobile devices, WeChat has enjoyed great popularity among college students and teachers and has been considered as a useful mobile English learning tool, because of its convenient method of operation and its unique features of sending and sharing texts, voices, pictures, videos, web links and so forth.However, the numerous potential distractions have also turned WeChat platform into a double-edged sword for college students when it comes to self-regulated learning.This study investigates the situation of college students' mobile English learning based on WeChat from the perspective of metacognitive strategies, which include self-planning, self-monitoring and self-evaluating through questionnaire.Figuring out the current situation of the mobile college students' English learning based on WeChat, this study finds that the college teachers' and students' knowledge of this new paradigm of learning and their awareness of how to apply it are still insufficient.Besides, the levels of students' using meta-cognitive strategies are generally not high enough, and students' gender and major also have an influence on the levels of the three meta-cognitive strategies.
Some Applications of Coding Theory in the Projective Plane of Order Four

The main aim of this research is to introduce the relationship between the topic of coding theory and the projective plane of order four. The maximum value of size code M over the finite field of order four and an incidence matrix with the parameters, n (length of code), d (minimum distance of code) and e (error-correcting of code) have been constructed. Some examples and theorems have been given.
Deep Learning in Person Re-identification for Cyber-Physical Surveillance Systems

The Cyber-physical Systems (CPS) are a combination of integrated physical processes, networking and computation to be minored and controlled y embedded subsystems via networked systems with feedback loops to change their behaviour when needed. Whilst the increased use of CPS brings more threats to the public, and thus security problems in this area have become a global issue to make it necessary to develop new approaches for securing CPS. The CPS utilise three-level architecture based on the respective functions of each layer: the perception layer, the transmission layer, and the application layer. Security in specific, CPS applications is currently the most important security objective of CPS because it offers the importance of CPS in its improving functionality This chapter focuses on the application aspect which is more related to people’s daily lives, and will present a real-time system including distributed multi-camera system that integrates computing and communicating capabilities with monitoring on people in the physical world, namely person re-identification in the cyber-physical surveillance systems. The increasing sophistication and diversity of threats to public security have been causing a critical demand for the development and deployment of reliable, secure, and time-efficient visual intelligent surveillance systems in smart cities. For example, visual surveillance for indoor environments, like metro stations, plays an important role both in the assurance of safety conditions for the public and in the management of the transport network. Recent progress in computer vision techniques and related visual analytics offers new prospects for an intelligent surveillance system. A major recent development is the massive success resulting from using deep learning techniques to enable a significant boosting to visual analysis performance and initiate new research directions to understand visual content. For example, convolutional neural networks have demonstrated superiority on modelling high-level visual concepts. It is expected that the development of deep learning and its related visual analytic methodologies would further influence the field of intelligent surveillance systems. In view of the high demand for a prevalent surveillance system by the metropolis communities, this chapter will introduce recent research based on deep neural networks and pipelines to the practitioners and human investigators undertaking forensic and security analysis of large volumes of open-world CCTV video data sourced from a large distributed multi-camera network covering complex urban environments with transport links. This chapter will address the challenges of using deep learning and related techniques to understand and promote the use of ubiquitous intelligent surveillance systems.
Memupuk Minat Baca Anak

This article discusses about fostering children's reading interest. The research method used is, looking for sources in the library (Library Research), Observation (Observation), and question and answer (Questionnaire). School libraries can be used as a source of learning for students, both in the process of teaching and learning activities in formal and non-formal ways to help schools in their efforts to achieve educational goals in the school. If the teacher's high reading interest will be easier and lighter in carrying out his duties. Children will be more active, seek and explore knowledge. Keywords: reading interest, children, school library
Pengembangan media komik dengan metode picture and picture untuk meningkatkan keterampilan literasi matematika kelas IV

AbstractIn Indonesia, mathematical literacy in International scope is still not satisfying. In order to increase mathematical literacy ability, it can be done by applying some variation of learning methods supported by the utilization of learning media. The goal of this study is to develop and examine the validity, the practicality, and the effectiveness of comic media by picture and picture method to increase mathematical literacy ability of grade 6th students. This R&amp;D study used the ADDIE development model combined with steps in making comics by Sadiman. Those steps were analysis (analyzing the needs, goal and main material), design (synopsis, first step), development (prototype product, evaluation, revision, and last script), implementation (trials), and evaluation (final product). The validity of the product could be seen from expert judgment by using material, media, and learning expert validation instrument. The practicality of the product was done by the students’ response questionnaire instrument to the media. The effectiveness of the product was seen from one class trial by one group pre-test post-test, and the result was processed using Paired-Samples T-Test check with the help of SPSS 20.0. The result of this study was the comics media to increase grade 6th students’ mathematical literacy ability. Comics media proved to be valid from material and media aspects. Comics media proved to be practice from students’ response questionnaire. Comics media also proved to be effective based on the result of the pre-test, post-test and Paired-Samples T-Test check.Keywords: Comics, Mathematical Literacy, Picture and Picture
The Unsupervised Learning Algorithm for Detecting Ellipsoid Objects

This paper is devoted to the analysis and implementation of the algorithms for automatic detection of the circular objects in the image.The practical aim of this task is development of the algorithm for automatic detection of log abuts in the images of roundwood batches.Based on literature review four methods were chosen for the further analysis and the best performance out of them was provided by ELSD algorithm.Some modifications were implemented to the algorithm to fulfill the requirements of the given task.After all, the modified ELSD algorithm was tested on the dataset of the images.The relative accuracy of the algorithm in comparison with manual measurement is 95.2% for the images with total area of background scene less than 20%.
Fast Exhaustive Search Algorithm for Discovering Relevant Association Rules

Association Rules Mining (ARM) is one of the most important tasks of Data mining.The purpose of ARM is to discover relationships having an interest between attributes/patterns stored in very large databases.Nowadays several efficient algorithms have been developed by the researchers for the discovery of relevant Association Rules (ARs).These latter are responsible for decision making in several domains, such as medicine, finance, marketing and many other fields.In this paper, we propose a new algorithm based on exhaustive search to find relevant AR to make the decision and to predict the chance of occurring the Diabetes Mellitus (DM).We develop an algorithm to mine data in less time and less complexity without losing information.Finally, we test our approach using a real database to evaluate the efficiency of our algorithm compared to Apriori algorithm.
THE MAIN CHARACTER’S ANXIETY DISORDER IN THE NOVEL BLUE SKIES BY CATHERINE ANDERSON

ABSTRACTThe purpose of this research is to show the type of anxiety and the psychological impact on the main character in the novel Blue Skies by Catherine Anderson. The method used to conduct this research is descriptive analysis whilst the technique is library research. Besides that, this paper also applies intrinsic approach in the process of the analysis, such as character and characterization, setting and conflict as well as extrinsic approach which is the theory of psychoanalysis by Sigmund Freud. Carly Adams as the main character is identified to experience a lot of anxiety problems namely neurotic, realistic and morality anxiety. Those anxieties have given psychological impact on Carly’s life. However, at the end, the main character is able to control her anxiety problem. Keywords : Physcological Problem, Anxiety, Psychoanalysis
An Initial Framework of Fuzzy Neural Network Approach for Online Learner Verification Process

Online learning is become more popular among university due to its flexibility and adaptability.The student authentication as online learner is widely seen as a major concern for online assessment.In most cases, there is absent of face-to-face supervision during online assessment, this situation leads the student to use or find help from others in order to get high scores in their result.This paper address the issue related to online assessment.The main objective of this work was to propose the use of online learner verification framework.This proposed solution utilizes the keystroke analysis and activity-based authentication for the online learner authentication.A fuzzy neural network is used to train and validate the online learner's identity.The proposed framework can be implementing in any online learning environment for verifying online learner identity.
PENINGKATAN KEMAMPUAN BERBAHASA ANAK USIA 5-6 TAHUN MELALUI PERMAINAN MEDIA KARTU HURUF BERGAMBAR DI TK PELANGI TENGGARONG SEBERANG TAHUN PEMBELAJARAN 2016-2017

This study aims to find out how to improve the language skills of children aged 5-6 years through playing illustrated letter card media at Pelangi Tenggarong Seberang Kindergarten in the 2016/2017 learning year. This type of research uses the class action research method (CAR) carried out in two cycles. The object of this research is 20 children. Research data collection uses observation sheets while the results are analyzed using quantitative descriptive methods. The results of data analysis showed that there was an increase in pre-cycle to the first cycle of 35%. In the second cycle increased 91.11%. The conclusion in this study, that the use of pictorial letter card media can improve language skills in children aged 5-6 years in Pelangi Kindergarten.
Towards a Data-Driven Approach for Fraud Detection in the Social Insurance Field: A Case Study in Upper Austria

The Social Insurance industry can be considered as a basic pillar of the welfare state in many countries around the world. However, there is not much public research work on how to prevent social fraud. And the few published works are oriented towards detecting fraud on the side of the employees or providers. In this work, our aim is to describe our experience when designing and implementing a data-driven approach for fraud detection but in relation to employers not meeting their obligations. In fact, we present here a case study in Upper Austria but from which interesting lessons can be drawn to be applied in a wide range of different situations.
Neural Style Transfer with Content Discrimination

Neural style transfer, which creates fantastically stylized images by separating and recombining the content and style, has received much attention in both academic and industrial applications. Thus, how to separate and recombine the content and style is of critical importance. However, most of existing neural style transfer algorithms attempt to stylize the content images uniformly without considering the variations of content details, thus sometimes producing visually unpleasing images. To address this problem, we propose a novel content-aware neural style transfer algorithm by taking account of variations of image contents (e.g., smooth, salient regions). To this end, our method first divides the content image into different regions based on salient information and then stylizes different regions discriminatively. Such a content-aware way of transfer retains more identifiability of the subject in the content image resulting in higher appreciable value in image quality than general transfer. Experiments demonstrate the effectiveness of our method.
Penelitian perancangan sarana bantu belajar bahasa untuk anak tunarungu dengan pendekatan participatory design

This research focused on deaf students in the third year of junior high school. When communicating in writing the structure of the grammar of deaf students is often reversed, ironically, they’re expected to pass on national test for normal students. This study uses a participatory design approach because all stakeholders involved in the design process are considered as coworkers in decision making. The designer, teacher and student are the stakeholders involved in this research. The group discussion forum was conducted to understand the types of games that are easy but fun to play for deaf students and to get feedback and recommendations for improvements from the games that have been made. This study produced language learning aids in the form of educational grammar games for third-year deaf students of junior high school. The theme of the grammar game that was appointed was adapted to the practical lessons at Yayasan Karya Dharma Wanita (YKDW), namely cooking and salons. The results of the study were tested in another deaf school which is Pangudi Luhur and the results were obtained that the product could be well received, even though they have different educational approach from YDKW. This study finally concluded that in Indonesia there isn’t standardization regarding the deaf kid’s education system. Key words : product design, language learning tools, deafness
Multilingual Focused Crawler System based on Web Content Extraction and Path Configuration

Abstract The multilingual focused crawler system combines web content extraction with path configuration to make use of their advantages and achieve automatic collection of network information in multiple languages. Firstly, system selects foreign language keywords according to crawling webpage language and Chinese keywords, and uses initial link to obtain webpage information. Then, it uses path configuration information or web content extraction algorithm based on the distribution line block to get webpage content, and adopts rules or configuration information to acquire new links, published time and title. Next, keywords are used to filter irrelevant information. Finally, results are presented as a list. When users use focused crawler system, the webpage path information can be configured or not according to requirements, and the collected network resources can also be searched or filtered.
Embedded Flower Pollination Evolutionary Programming Based Technique for Voltage Stability Enhancement with Distributed Generation Installation

This paper presents the embedded flower pollination evolutionary programming-based technique for voltage stability enhancement with distributed generation installation.In this study, a new technique is developed which combines the element of flower pollination into the general evolutionary programming algorithm.The aim is to enhance the voltage stability in power system with the presence of distributed generation.The proposed technique was validated using the IEEE 33-Bus Distribution System.Results obtained from the study revealed that the proposed technique is better than EP in terms of optimizing the sizing of DG and location.
SOCIAL STUDIES LEARNING MEDIA BASED ON MOBILE LEARNING APPLICATION FOR ELEMENTARY SCHOOL STUDENTS

Tujuan penelitian yaitu mendeskripsikan produk dan menjelaskan penggunaan media pembelajaran IPS berbasis aplikasi mobile learning dengan pendekatan social constructivism yang dihasilkan bagi siswa sekolah dasar. Penelitian ini menggunakan pendekatan kualitatif dengan metode studi pustaka serta jenis penelitian deskriptif. Data utama diperoleh dari buku, jurnal, artikel, dan catatan harian penelitian. Hasil penelitian yakni media pembelajaran IPS berbasis aplikasi mobile learning yang dihasilkan bagi siswa sekolah dasar berupa komik, gambar berseri, dan poster yang dikemas dalam program Edmodo. Edmodo merupakan aplikasi yang menarik dengan elemen sosial berupa aplikasi edukasi berbasis jejaring sosial. Akun Edmodo dapat dibuat oleh guru, siswa dan orang tua yang berbasis cloud kolaborasi dengan aplikasi yang cukup aman digunakan untuk kelompok terbatas. The objective of the research is to describe the learning media product learning of social studies based on mobile learning application with social constructivism approach which is produced for elementary school students and explain the use of social studies learning media based on mobile learning application with social constructivism approach for elementary school students. This research uses qualitative approach with literature study method and descriptive research type. The main data were obtained from books, journals, articles, and research diaries. The result of research is learning media of social studies based on mobile learning application that produced for elementary school students in the form of comics, serial images, and posters that are packed in Edmodo program. The resulting comic tells the economic activities carried out by the characters. The resulting image contains the sub subject matter of globalization around me. The learning consists of content of social studies subjects (globalization), sains (energy change) and Indonesian (using standard and coherent vocabulary). Edmodo is an interesting application with social elements in the form of educational applications based on social networking. Edmodo accounts can be created by collaborative cloud-based teachers, students and parents with applications that are safe enough to use for restricted groups. Groups created by teachers, students and parents can sign in with a dedicated account. Teachers provide learning tools as well as learning process planning. Students and parents can access learning wherever and whenever. Students are able to establish social interaction with friends in groups or teachers as a form of discovery and discussion of knowledge. Parents as controlling the access and implementation of learning by students. DOI: http://dx.doi.org/10.17977/um020v13i12019p97
Hyb-Tvx: A Hybrid Semantic Similarity Feature-Based Measurement for Multiple Ontologies

Semantic similarity is defined as the closeness of two concepts, based on the likeliness of their meaning.It is also more ontology-based, due to their efficiency, scalability, lack of constraints and the availability of large ontologies.However, ontology-based semantic similarity is hampered by the fact that it depends on the overall scope and detail of the background ontology.This leads to insufficient knowledge, miss-ing terms and inaccuracy.This limitation can be overcome by exploiting multiple ontologies.Semantic similarity with multiple ontologies potentially leads to better accuracy because it is able to calculate the similarity of these missing terms from the combination of multiple knowledge sources.This research aims to develop and evaluate a feature-based mechanism (Hyb-TvX) to measure semantic similarity with multiple ontologies which can improve the accuracy of the similarity.Similarity value, correlation and p-value were also used in the evalua-tion of the relationship between the concept pair of multiple ontologies.Besides that, the Hyb-TvX mechanism produces the highest correla-tion value compared to the other two methods, that is 0.759 and the result correlation is significant..
Correction to: Factors that affect the success of learning analytics dashboards

The Funding information provided in this article as published stands in need of correction. The correct information is: “This study was supported by research fund from Honam University, 2017”. Also note the current correct affiliation for author Yeonjeong Park: Department of Early Childhood Education, College of Humanities and Social Sciences, Honam University, Gwangju, South Korea