Reviewerly/exHarmony huggingface dataset:
A Teaching Software of Chinese Character Structural Layout Based on Mobile Device

In order to achieve the intelligent teaching of Chinese character writing, a teaching software for Chinese character structural layouts is designed and implemented. It supports mobile device such as mobile phones, tablets and so on. So, it is suitable for learning occasions anytime and anywhere. In the aspect of function design, 14 types of structural layouts are summarized, and their corresponding evaluation algorithms and animation feedback are developed. Therefore, the tool realizes the integration of computer evaluation technology and traditional writing teaching rules. The experimental results show that the tool has played a good auxiliary role in the teaching of Chinese character structural layout.
COVARIANCE BASED-SEM ON RELATIONSHIP BETWEEN DIGITAL LITERACY, USE OF E-RESOURCES, AND READING CULTURE OF STUDENTS

In this paper, a relationship model among latent variables using Covariance Based-Structural Equation Modeling (CB-SEM) is studied. The latent variables are digital literacy, use of e-resources and reading culture of students. The goal of the study is to build a simultaneously model between those three variables, determine the influence of digital literacy on the use of e-resources and reading culture of students, and the influence of the use of e-resources on reading culture of students. The parameters of the model are estimated by the Maximum Likelihood method. This study took data from 256 questionnaires of students at STMIK Sumedang. Results showed that digital literacy significantly influences the use of e-resources and the reading culture of students. In contrast, there are no significant influences on the use of e-resources on the reading culture of the student.
MATHEMATICAL MODEL BASED INTERACTIVE SIMULATIONS IN EDUCATION

Appears in: ICERI2019 Proceedings Publication year: 2019Pages: 10120-10125ISBN: 978-84-09-14755-7ISSN: 2340-1095doi: 10.21125/iceri.2019.2479Conference name: 12th annual International Conference of Education, Research and InnovationDates: 11-13 November, 2019Location: Seville, Spain
The Plastic Crisis Goes Public: Representations of Plastic Pollution in Environmental Media

Plastic pollution emerged as a landmark environmental issue in the last few years, and as such, has appeared in environmental media. This thesis examines the representations of plastic pollution in environmental communication campaigns, social media of Non-Governmental Organizations (NGOs), environmental campaigns created by the advertising industry, corporate environmentalism efforts, and media from concerned individuals. While plastic materials began as a way to mimic materials found in nature, their ubiquity, heavy promotion from petrochemical companies, and widespread adoption as single-use disposables outpaced waste disposal measures. NGOs and nonprofits unite under networked environmental campaigns, invoke agenda-setting theory, and favor framing that features ocean life and marine debris. Single-use plastic straws, spurred by a viral video of a sea turtle and work from organizations like Lonely Whale, have become emblematic of plastic pollution as a whole. Plastic pollution campaigns from NGOs and advertisers and often lack clarity and calls-to-action. Among the corporations embracing anti-plastic efforts, Starbucks, Adidas, and 4ocean have differing levels of greenwashing and may or may not create a social energy penalty. Irony and self-reflexivity, as well as plastic pollution's connection to climate change, may provide avenues for environmental communication. System-based anti-plastic communication and efforts may have more of an impact than those that promote individual lifestyle changes and focus on a single item.
FACTORS INFLUENCING DEVELOPMENT OF READING LITERACY IN MOTHER TONGUE AND FOREIGN LANGUAGE

Appears in: ICERI2019 Proceedings Publication year: 2019Pages: 6901-6907ISBN: 978-84-09-14755-7ISSN: 2340-1095doi: 10.21125/iceri.2019.1644Conference name: 12th annual International Conference of Education, Research and InnovationDates: 11-13 November, 2019Location: Seville, Spain
A Hybrid Framework for Problem Solving of Comparative Questions

Comparative questions in Chinese, as a special and complex form of question answering (QA), have their own unique sentence structure, existing methods cannot solve them well. Inspired by cognitive studies on how humans solve complex problems, we propose a hybrid framework which combines Logic Programming and attention based Bi-LSTM. This framework is decomposed into three consecutive components: 1) identify comparative questions, 2) extract comparative elements from the identified comparative questions, and 3) answer factoid questions containing the extracted comparative elements. Specifically, for the former two components, Logic Programming is adopted to filter out non-comparative questions and extract comparative elements. For the latter one, a bidirectional long and short term memory (Bi-LSTM) model with attention mechanism is utilized. Experimental results on Chinese geographical question datasets show that our proposed hybrid framework achieves outstanding performance for practical use.
RANCANG BANGUN SISTEM INFORMASI PENILAIAN KINERJA TENAGA PENDIDIK DI FAKULTAS TEKNIK DAN SAINS UNIVERSITAS IBN KHALDUN

The performance appraisal system is a system to evaluate all resources whether those resources have run following the standards set by management in achieving its objectives. But the need for a mechanism that can facilitate the process of evaluating the performance of educators, and the results of the performance appraisal need to be recorded on an information technology system so that the process of evaluating the performance of educators can be processed quickly and objectively is still an obstacle. The purpose of this study is to obtain an application system design assessment of the performance of educators. The waterfall is a method used in system development. The 360-degree method and k-nearest neighbour are used as models to calculate the performance appraisal of the teaching staff. Sources of data in this study include Questionnaire, DP3 (Daftar penilaian pelaksanaan pekerjaan pegawai). The results of this study are the application of the teacher performance appraisal system has met the feasibility based on black box testing and can assess the performance of educators quickly and objectively.
APLIKASI PENGENALAN KEBUDAYAAN JAWA BERBASIS DESKTOP

Nowadays, technology has a big impact for lifes. It also makes children like to use technology to watch videos, play games and socialize through the media. In addition to that technology, they are more familiar with foreign culture compared to their own culture. The habit itself is very related to daily activities using smart phones via the internet. Likewise, the introduction of culture in Java for desktop-based elementary school children is still very rare today. The making of this application is a solution to provide knowledge about diverse cultures in Java. With this application it is hoped that children will get to know their own country's culture more than foreign cultures. Thus, it can create a feeling of love for the nation itself. The desktop application that is served is an application that supports a culture consisting of various menus to facilitate users who open this application with those connected to the internet, using a system development method called waterfall which is system planning, system design, code conversion, system testing and good assistance. In this research, an application in desktop platform was successfully created and from the evaluation it is useful for children and students in learning Java culture.
The Impact of Blockchain-Bitcoin in Malaysian Markets

In field of technological advance, when everyone talks about the Internet of thingsâ€, and so it is expected that there is something and everything in relationship, money should not be left. The currency of papers is a thing of past, since virtual currencies are beginning to take control and Bitcoin is ready to achieve this performance. Not only does it revolutionize way it is paid, but it also potentially affects USD as USD, which is already a challenge for challenges of EURO or Chinese Renminbi Yuan (CNY). The increase in crypto currencies will give a new dimension to this challenge for Ringgit (MYR) in Malaysia. The purpose of this study is to understand many factors that are gaining momentum in Bitcoin (BTC) in several areas of global finance and how confusing it can be, including financial system of major fiduciary currencies, which is mainly MYRs. The most important variables examined are Bitcoin, Bitcoin Technology, Bitcoin Economy and Bitcoin as currency. Furthermore, study would propose a framework that would become foundation for furthering of upcoming explorations. Finally, this study would act as a stepping ground for making effective contributions towards understanding best possible way to plan for success of retail market in Malaysia.
Aleurite particle saltation modeling

Aleurite particle saltation trajectories have been calculated using the saltation dynamics model. Variability of the saltation trajectory parameters including of the height, range and particle flight time was analyzed. Saltation parameter dependencies from particle diameter and the friction velocity are approximated. Influence the lift-off velocity and the lift-off angle on the aleurite particle saltation trajectories was considered. Sliding coefficient dependencies from time during aleurite saltating particle transport were received for the various values of the particle diameter, friction velocity, lift-off velocity and lift-off angle.
A Cloud based CRM Architecture for Neural Network Inventory Control

In this paper, a novel cloud based CRM (Customer Relationship Management) framework is proposed for neural network inventory control which can help the enterprise about future plans of their inventory. The framework is about predicting the needs of product based on past history on paid invoices. Paid invoices are selected according to events occurred at different time period. The framework proposed in this paper is REST (Representational State Transfer) based where machine learning algorithm for neural network is on separate host and input data is then given from cloud CRM as JSON (JavaScript Object Notation) messages. The framework can be installed as App/ Extension/ Module/ Solution in CRM.
An Analysis of Interlingual and Intralingual Errors in EFL Learners’ Composition

&lt;p class="abstrak"&gt;&lt;em&gt;This study aims to investigate the occurrence of errors committed by EFL learners in their composition in terms of interlingual and intralingual errors. The setting of the study was a state Islamic university in Banjarmasin South Kalimantan, Indonesia. The research participants were undergraduate students majoring in English Education. Data were collected &lt;/em&gt;&lt;em&gt;through&lt;/em&gt;&lt;em&gt; documentation of students’ composition and analyzed based on Corder’s Error Analysis (EA) theory. From the samples of 38 compositions submitted, it was identified that interlingual errors occurred more frequently than intralingual errors. Interlingual errors comprised morphological selection, lexical selection, syntactical selection, and misordering. Meanwhile, intralingual errors were evident in both omission and addition in the areas of word formation and syntax. The findings of this study revealed that first language interference caused more errors in writing than learners’ incomplete process of acquiring second language rules. To prevent the errors from being fossilized, it is suggested that in the teaching and learning process, language instructors provide continuous corrective feedback, and learners be more active in finding exposure to the correct form of the target language.&lt;/em&gt;&lt;em&gt;&lt;/em&gt;&lt;/p&gt;&lt;p class="StyleAuthorBold"&gt;Abstrak&lt;/p&gt;&lt;p class="abstrak"&gt;Penelitian ini bertujuan untuk menyelidiki terjadinya kesalahan yang dilakukan oleh pembelajar bahasa asing dalam tulisan mereka yang berupa kesalahan interlingual dan intralingual. Penelitian dilakukan di sebuah universitas Islam negeri di Banjarmasin Kalimantan Selatan Indonesia. Partisipan penelitian adalah mahasiswa S1 jurusan Pendidikan Bahasa Inggris. Data diperoleh melalui dokumentasi hasil karangan mahasiswa yang kemudian dianalisa berdasarkan teori Error Analysis dari Corder. Sebanyak 38 sampel karangan mahasiswa dikumpulkan dan ditemukan bahwa kesalahan interlingual lebih banyak terjadi daripada kesalahan intralingual. Kesalahan interlingual berupa kesalahan dalam memilih kosa kata dan menyusun kalimat yang disebabkan oleh pengaruh bahasa asli. Sedangkan kesalahan intralingual berupa penghilangan atau penambahan yang tidak tepat pada bentuk kata atau bentuk kalimat. Hasil penelitian menunjukkan bahwa pengaruh bahasa asli yang menyebabkan kesalahan interlingual dalam tulisan terjadi lebih banyak daripada kesalahan intralingual. Untuk mencegah melekatnya kesalahan, disarankan agar dalam proses belajar mengajar guru dapat terus memberikan umpan balik, dan siswa harus lebih aktif dalam mencari contoh-contoh bentuk bahasa yang benar.&lt;/p&gt;&lt;p class="abstrak"&gt;&lt;strong&gt;Kata Kunci: &lt;/strong&gt;kesalahan, interlingual, intralingual, karangan&lt;/p&gt;
An Empirical Investigation of Performances of Different Word Embedding Algorithms in Comment Clustering

With the rapid growth of the usage and interest in social network services, evaluating comment clustering has become increasingly important for various commercial and scientific applications. Analyzing, organizing and ascertaining the overall theme of a large volume of comments is a challenging and time-consuming task which has attracted much attention recently. In this study, we proposed a method to address the comment clustering problem. Extensive experiments have been conducted on seven different comment datasets using TF-IDF and different word embedding algorithms, namely Word2vec, Glove and FastText; the internal clustering validation have been conducted to evaluate the performance of each method in clustering of the comments. We observed that word embedding produced significantly better results in comment clustering than TF-IDF. In addition, word2vec has shown the best performance among all; however, we found that Glove is the most stable and consistent across all datasets such that the performance improved as dataset size increased.
Research of System Fault Diagnosis Method Based on Imbalanced Data

For the training of multiple models, the performance of single algorithm will be unstable, and an adaptive imbalance classification algorithm is proposed. The algorithm combines the area under curve (AUC) value to optimize the support vector description algorithm, the random forest algorithm and the gradient boosting decision tree algorithm respectively to generate the sub-model for classification. This paper uses the model fusion method to generate the sub-model for fusion. Finally, this paper selects the optimal sub-model to get stable classification results based on the AUC value. The algorithm in this paper is verified on the equipment running data set published by the American Prognostic and Health Management (PHM) Society in 2015. The result shows that the fault recognition rate is higher than that of the single imbalance classification algorithm. The classification effect is superior and the performance is stable.
Statistical significance in the era of big data

The development of new technologies has affected both the procedures of traditional statistical surveys and the perception of their results in the light of other availa-ble sources of information. In this connection, the roleof the verification of statistical hypotheses and of the interpretation and presentation of its results, including the use of statistical significance and p-value, has recently returned as a frequent topic for discussion among the scientific community. The author was inspired to write this paper by a wave of discussion regarding this matter held at the beginning of 2019 in the Natureand The American Statistician journals. The aim of the paper is to present the opportunities provided and challenges posedby the use of big data to the hypothesis verification process and to statistical inference, both in the traditional and Bayesian approaches. The author explains the necessity of discontinuing adopting excessivesimplifications while performing statisticalinference and pre-senting the results of the verification of hypotheses. This involves both the postulate to pay greater attention tothe quality of sampling data, especially in the case of data originating from big data sets, as well as the postulate to providefull information about the statistical model on the basis of which the inference is being performed.
Technology for the development and use of electronic educational resources in the educational process of a university

Purpose of the study. The aim of the work is to consider the possibility of improving the quality and accessibility of teaching and educational resources through the development and use of electronic educational resources (hereinafter referred to as EER) using the example of the module “System Design”. The article presents a solution to the problem that is of significant importance in the field of information technology implementation in education. The relevance of the research problem is determined by the fact that through the use of interactive tools in the learning process, users, as a rule, a student and an educator, can actively interact with these information tools. Interactivity implies the existence of conditions for educational dialogue, one of the participants of which is a means of informatization of education. Materials and methods. To solve these tasks, the general scientific system approach was used as the main one, the basis of which is to consider educational facilities as systems functioning in a certain environment, as well as methods of analysis and comparison. The study was conducted in accordance with the pedagogical conditions of student learning and the methodological requirements for the educational product. We reviewed methodological recommendations on the use of e-learning in the educational process of the university, the main regulatory documents of distance education technologies in the implementation of additional professional programs, the Moodle distance learning system, guidelines for practical exercises, as well as reference materials on the Moodle system. Results. The study revealed the problem of the use of electronic educational resources, their positive and somewhat negative impact on the goals and results of the educational process, as well as existing technologies for their creation. Based on the analysis of a variety of development technologies for various characteristics, a decision was made to use the LMS Moodle environment. The structure of the module “System Design” was developed, and this module was implemented in the LMS Moodle environment and tested in the educational process, it was revealed that the level of knowledge and skills mastering, as well as their possession is higher among students who studied on the electronic educational resource. Conclusion. Thus, the results of the study allow us to recommend the introduction of electronic educational resources in the learning process. Since the use of the presented development will not interrupt the learning process in cases where the student can not attend classes, and also contributes to improving the formation of students’ competence level.
EAC-Net: Efficient and Accurate Convolutional Network for Video Recognition

Research for computation-efficient video understanding is of great importance to real-world deployment. However, most of high-performance approaches are too computationally expensive for practical application. Though several efficiency oriented works are proposed, they inevitably suffer degradation of performance in terms of accuracy. In this paper, we explore a new architecture EAC-Net, enjoying both high efficiency and high performance. Specifically, we propose Motion Guided Temporal Encode (MGTE) blocks for temporal modeling, which exploits motion information and temporal relations among neighbor frames. EAC-Net is then constructed by inserting multiple MGTE blocks to common 2D CNNs. Furthermore, we proposed Atrous Temporal Encode (ATE) block for capturing long-term temporal relations at multiple time scales for further enhancing representation power of EAC-Net. Through experiments on Kinetics, our EAC-Nets achieved better results than TSM models with fewer FLOPs. With same 2D backbones, EAC-Nets outperformed Non-Local I3D counterparts by achieving higher accuracy with only about 7× fewer FLOPs. On Something-Something-V1 dataset, EAC-Net achieved 47% top-1 accuracy with 70G FLOPs which is 0.9% more accurate and 8× less FLOPs than that of Non-Local I3D+GCN.
Complex Analysis of Political Speech

Despite being a country of various blue stockings, Indian daughters particularly from the countryside and lower socio-economic hierarchy have remained the victims of unfairness in learning opportunities from ancient to modern time.The present research work tries to examine the regional progress and inequality in education and determinants of lower educational prospects of girls in India on the basis of secondary data.Here, the disparity index and correlation coefficient are applied to analyze the gender discrepancy of education and the relationship between literacy and its major determinants respectively.It has been examined that despite the celebration of longtime independence, it is very distrustful to accept that one fourth proportion of the population of the country is not capable to read and write to an easy cohesion of words with understanding in any of language.Though various plans have been launched with prime target of enhancing the female literacy, yet in all over the nation, the disparity in literacy still exists which demands some impressive efforts for bringing the equity.
Authentication by Graphical Passwords Method ‘Hope’

The security of data and user authentication is an important component of currently deployed security infrastructures. Typical text-based passwords and PIN codes have several drawbacks. Whilst short passwords are easy to remember they are insecure, whereas longer complex passwords are more secure but more difficult to remember. The disadvantage of user authentication systems can be solved by replacing typical alphanumeric passwords with a method using graphical passwords comprising images, which can be easily recognized by the user [1]. A mechanism was developed that makes use of graphically based passwords. A web-based prototype application was implemented that makes use of the new authentication mechanism.
A comparative analysis of the travelling salesman problem: Exact and machine learning techniques

Given a set of locations or cities and the cost of travel between each location, the task is to find the optimal tour that will visit each locations exactly once and return to the starting location.We solved a routing problem with focus on Travelling Salesman Problem using two algorithms.The task of choosing the algorithm that gives optimal result is difficult to accomplish in practice.However, most of the traditional methods are computationally bulky and with the rise of machine learning algorithms, which gives a near optimal solution.This paper studied two methods: branch-and-cut and machine learning methods.In the machine learning method, we used neural networks and reinforcement learning with 2-opt to train a recurrent network that predict a distribution of different location permutations using the negative tour-length as the reward signal and policy gradient to optimize the parameters of recurrent network.The improved machine learning with 2-opt give near-optimal results on 2D Euclidean with upto 200 nodes.