Reviewerly/exHarmony huggingface dataset:
Penerapan Algoritma Naïve Bayes Untuk Melakukan Analisis Sentimen Pada PT Pos Indonesia (Persero)

Pos Indonesia is the oldest shipping service that is widely known to the public, so it has different opinions on the performance of postal expeditions. The author identifies the problem in this research, namely the public's sentiment on the services of PT. Pos Indonesia (Persero) which is found on the Twitter social media platform and the number of positive or negative sentiments towards the services of PT. Pos Indonesia (Persero).&#x0D; Researchers use social media Twitter as a medium to get data to examine the performance of the Indonesian Post. In this research, the writer intends to analyze the sentiment towards PT. POS Indonesia (Persero) as an identification material for negative and positive opinions by using the nave Bayes algorithm to determine the service performance of PT. POS Indonesia (Persero). Researchers also use CRISP-DM as a data processing method and use rapid miner applications to obtain, process and produce positive and negative classifications. Classification of data in this study took 141 tweets discussing PT. POS Indonesia (Persero) on Twitter media by using the keyword Pos Indonesia. The results of this study resulted in a positive sentiment value of 63% and a negative 37%. With the highest accuracy, the 80:20 data split method uses the Naive Bayes algorithm of 64.29%.
Knowledge Representation in Multilingual Education Resources

Introduction. Ontologies are now recognised as the advanced standard of knowledge representation for e-learning and some industries. In particular, the development of multilingual ontological education resources is characterised as a promising area of research in the context of industry universities’ digital transformation. The article deals with the development of an academic course multilingual ontology in a Controlled Natural Language. Relevance. Although there are many ontology editors, national developers of education resources should be familiar with formal logic and have a good command of English. Therefore, it is difficult to discuss widespread use of ontology-based education solutions in Russian universities. Materials and Methods. The article offers a version of Controlled Russian Language for academic knowledge representation. A methodology to be used for compiling academic course ontologies is developed. As an example, a piece of ontology for the Introductory Course on Railways is considered. Results and Discussion. To support this way of knowledge representation, a prototype of ontology editor Onto.plus was developed to support the version of Controlled Russian Language. To implement the multilanguage function, equivalent versions for the Controlled Russian Language ontology were developed in English and Chinese. Conclusions. The solutions are a contribution to the implementation of an open project to develop an ontology resource integrating universities and industry.
The Study of Selection Bottle Packaging for Carbonated Beverages

The growth of the packaged beverages market in Indonesia is overgrowing. One sector of packaged beverages is carbonated beverages and bottled water. The main problem with packaged beverages containing dissolved gases is maintaining product quality during shelf life. Packaging materials and packaging lids cause a decrease in dissolved gas levels in beverages. Therefore, this study aims to analyze leaks in polyethylene terephthalate and glass bottles so that can use them to estimate the shelf life of the product. This study uses water, 3 types of glass bottles, and 1 type of plastic bottle. Bottles filled with water with various filling volumes of 40%v/v, 60%v/v, and 80%v/v were then analyzed for bottle leakage for 8 days. The results showed that effectively used a glass bottle with a volume of 250mL filled with more than 80%v/v, this was because it had the least leakage rate compared to others. In addition, this bottle has an attractive visual, easy labeling, and the size is not too large (ergonomic).
Strategies for Improving Memory in Students

Students generally have little to no understanding of the memory processes, resulting in an inability to study effectively. To perform better, it is imperative to take control of memory by understanding how memory works, how information can be committed to memory, and how forgetting can be avoided. Some insight into the cognitive load theory can also be applied to improve learning.
Design and implementation of Pedestrian detection based on Zynq APSoc

Pedestrian recognition is an important content of intelligent security surveillance video processing system. In order to meet the application requirements of miniaturization and real-time security system, a moving target recognition system based on APSoc platform is designed. The system uses ov5640 camera as the video collector, zynq7020 as the development platform, and uses the soft and hard co-design to realize each function module. Finally, the pedestrian image acquisition and real-time display system is successfully completed. The test results show that the system can effectively and stably track pedestrians and moving objects within a certain range of distance, and can be displayed in real time, miniaturized and low power consumption, which can be further applied in the field of security.
Application of eye movement tracking technology in web design

Eye movement tracking technology is an emerging technology in recent years and has been widely used in many fields. Tracking people’s eyeball movement can help to understand human’s emotion and behavior, reflect human’s subjective intention on things, and provide a basis for the research and development in many fields. This paper mainly reviewed the eyeball movement tracking technology, and made a brief analysis on its worldwide application, in order to lay a foundation for better understanding the research of eyeball movement tracking technology.
Crowd Counting Based on Context-Aware and Multi Scale Feature Fusion

Crowd counting plays an important role in public security. Estimating the number of people in an image with congested crowd accurately is a challenging task. The crowd counting method based on fully convolutional network can perform well in crowd image with complex scene. In this paper, to address the counting problems of occlusion，background clutter and perspective effect, we proposed a simple but effective method called Context-aware Multi scale Fusion Network(CMF Net).The CMF Net applied VGG network as backbone to extract coarse features. Then, three context-aware multi-scale fusion modules (CMFM) are adopted. Each CMFM consist of multi-scale feature extraction module (MEM) and context-aware feature extraction module (CEM). In addition, we propose adaptively dense connection to promoted information transmission in the counting network. Experiments on four datasets demonstrate that our network achieves competitive and effective results.
Novel Solution of Topological Recognition of Indoor Objects Based on Optical Flow and Planar Attributes

An approach of qualitative optical flow processing for indoor object recognition based on planar attributes is presented. The qualitative processing is performed under hierarchical segmentations of optical flow vectors. The proposed solution for indoor object recognition is undertaken from identifying planar and atilt properties of optical flow images. The advantages of the proposed solutions are the use of much simpler arithmetic to obtain more 3D details about indoor objects.
Attentive Pooling Network for Few-Shot Learning

Few-shot learning has become essential for generating neural network models that can generalize to novel classes given only a few labeled samples.Previous studies mostly focused only on building a class prototype via the relations between intra-class sample features and adopted the prototype to classify the target samples.Considering that the number of labeled samples is typically limited under few-shot settings, the use of these methods to produce representative prototypes for classification may not be efficient.To this end, in this study, we propose an attentive pooling network (APNet), which establishes the relationship between the prototype and target sample feature to highlight their important regions.APNet selectively assigns higher weights to the local features with higher relative importance scores in the prototype and the target feature map.By minimizing the classification loss through supervised learning, APNet learns to produce prototypes that are specific to the target feature based on the relative importance scores.To verify the effectiveness of APNet, we compared it with the existing methods on two popular few-shot learning datasets, and APNet outperforms the related methods by achieving 71.12% and 77.58% classification accuracy in the 5-shot setting on the miniImageNet and CUB datasets, respectively.
Developing Wix.Com Media to Improve Students’ Descriptive Text Writing Skills

This research aims to develop the learning media based on wix.com, to increase the students’ competence in descriptive text writing, and to find its validity and its effectiveness. The process of developing Production Écrite Avancée (PEA) learning material with wix.com is carried out in five stages; these are analysis, design, development, implementation and evaluation. The feasibility of PEA learning can be seen from the validation results. The results are rated 86.1% (very good) from material expert validation and 87.3% (very good) from the media expert validation. In addition, the result of the evaluation of the student questionnaire showed that the developed product obtained the rating of 86% (very good), so this product is valid or feasible. The result of the effectiveness of PEA learning with Wix.com shows that students’ pre-test and post-test increased. The students’ average score are 65 in the pre-test and 94 in the post-test. Progression exists in the students’ competence after learning and this is consistent with the results of the normality test. The pre- and post-test data have the value of Sig. 0.193 and Sig. 0.067 respectively. Since the sig. value for both data is &gt; 0.05 then, as the basis for decision making in the Shapiro wilk normality test where if the value of sig. is &gt; 0.05, there is a difference between pre-test and students’ positions. Hence, the students’ pre- and post-test data are normally distributed and increase their skills. This is also supported by the N-Gain test showing the average N-Gain score (g) of 0.51; the efficiency of the material learned with Wix.com is effectively used for PEA. Keywords: Writing, learning media, animation board, Benime
Reinforcement Learning with Information-Theoretic Actuation

Reinforcement Learning formalises an embodied agent's interaction with the environment through observations, rewards and actions. But where do the actions come from? Actions are often considered to represent something external, such as the movement of a limb, a chess piece, or more generally, the output of an actuator. In this work we explore and formalize a contrasting view, namely that actions are best thought of as the output of a sequence of internal choices with respect to an action model. This view is particularly well-suited for leveraging the recent advances in large sequence models as prior knowledge for multi-task reinforcement learning problems. Our main contribution in this work is to show how to augment the standard MDP formalism with a sequential notion of internal action using information-theoretic techniques, and that this leads to self-consistent definitions of both internal and external action value functions.
Instagram Post: Boosting Students’ Writing Achievement

This study looked into the use of Instagram to boost students' recount text writing achievement at MAN 2 Palembang. A quasi-experimental design was used, with an experimental and control group. A pre- and post-test was given to both (before and after treatment). Purposive sampling was used by the writers with 42 people in each group. Based on the paired-samples t-test with t-get &gt; t-table and a pre-test mean of 53.90 to 74.74 in the post-test, students' performance in writing recount has improved significantly. As a result, the sample t-test was intact by the experimental and control groups' post-test results, In the two-tailed degree-of-freedom test, the sig.level 0.05 output was 82, and the critical t-table value was 1.663 because the t value obtained 28.66 was greater than the critical value of t-table. Therefore, there was a significant difference between the tenth grade students’ writing achievement of Madrasah Aliyah Negeri 2 Palembang who were taught using Instagram and those who were not.
On binary LCD codes possessing an automorphism of order 13

In this work we apply the method for constructing binary LCD codes via an automorphism of prime order described in [3] and [4]. Thus we obtain all optimal LCD codes of lengths 26, 27 and 28 possessing an automorphism of order 13 with two cycles.
Application of digital technologies in kindergarten

The main subject matter of the paper is digital technology application in kindergarten as a result of the revolution of information technology since the 1980s. Author's ideas for the application of technological toys and applications in the kindergarten are shown. The current paper discusses children’s ability to apply digital technology in their day-to-day activities.
Practice-oriented teaching of mathematics as a cross line of model programs for grade 5-6 of the new ukrainian school

The article examines model curricula in mathematics for students of the 5th-6th grades. The ideas of the authors regarding the new trends in the content of the 5th-6th grade mathematics course of the New Ukrainian School and the pedagogical technologies of its teaching are analyzed. Conclusions were made about the orientation of model mathematics curricula for grades 5-6 on strengthening the practical and applied direction of the school mathematics course, increasing attention to the formation and development of key competencies. The article emphasizes the importance of revealing inter-subject and intra-subject connections during the teaching of mathematics to 5-6 grade students.
TEXT AND CONTEXT OF NEWSPAPER OPINION RUBRIC AND ITS UTILIZATION AS TEACHING MATERIALS IN SENIOR HIGH SCHOOL

This study aims to describe and explain: (1) aspects of the textual discourse of the opinion rubric in the Solopos newspaper, (2) the contextual aspects of the opinion rubric in the Solopos newspaper, and (3) the relevance of the textual and contextual aspects of the opinion rubric in the newspaper. Solopos news with teaching materials in high school. This study uses a qualitative descriptive research design with a content analysis approach. The data in this study are in the form of words, phrases, and sentences. The data sources used in this study are documents, namely the opinion rubric of the Solopos newspaper January-February 2021 edition, and the informants are Indonesian language teachers in class XII SMA, opinion writers, and opinion editors for the Solopos newspaper. Data collection techniques used, namely document analysis and interviews. Test the validity of the data using theoretical triangulation and data source triangulation. The data analysis technique used is the agih method. The results of this study indicate that: (1) textual aspects that support the integrity and cohesion of opinion discourse consist of grammatical cohesion and lexical cohesion; (2) contextual aspects of opinion discourse can be understood using the principle of personal interpretation, the principle of locational interpretation, and the principle of temporal interpretation; and (4) the opinion rubric for the January-February 2021 edition of the Solopos newspaper can be used as an alternative material for teaching editorial texts for class XII SMA.
Career satisfaction among staff at Alsayyed Muhammed Ben Ali Alssanusi University and its relation to certain variables

This study aimed to identify the level of job satisfaction among employees at Al - Sayyid Muhammad bin Ali Al - Senussi Islamic University "Faculty members_ Employees ", trying to find out the differences in the level of job satisfaction among them. The study used the descriptive approach, it was conducted on a sample consisting of "248" who were selected randomly, they were applied to the job satisfaction scale which is prepared by the researchers. Finally, the study reached a set of results, the most important of which are: The employees of this university enjoy a high degree of job satisfaction, it also showed that there are differences in the level of job satisfaction for university's employees, in front of faculty members over employees. In addition, there no significant differences in the level of job satisfaction for university's employees according to the gender change "males-females".
Deriving Modernity Signatures for PHP Systems with Static Analysis

The PHP language has undergone many changes in its syntax and grammar, with respect to both features the language has to offer as well as the distribution of language features used by programmers in their projects. We present a novel method of using grammar usage statistics to calculate a modernity signature for a PHP system, so that we can determine its age. The system will aid developers in choosing whether or not to execute or use a PHP system, without having to perform an extensive inspection.
Virtual Face Animation Generation Based on Conditional Generative Adversarial Networks

Face animation is to generate facial animation video with rich expression according to the target face image. Virtual face animation generation has always been a hot topic in the field of computer vision. How to generate real and natural virtual face animation has always been a key issue in this field. In this paper, facial feature points are used to describe different facial shapes, which are used as guidance conditions for generating target facial animations. By improving the Conditional Generation Adversarial Network(CGAN), high quality virtual facial animations are generated. At the same time, the MOS evaluation verifies the effectiveness of the model in generating characters by virtual face animation.
Augmented Reality Applications for Children to Learn English Alphabets

The modern era of smartphones and gadgets technology has become a human essential as to communicate, and different mobile application are been developed to make life easier. Hence, these smartphones and gadget will keep gradually upgrade from time to time and nowadays they are most commonly used by almost every age including the children. Nowadays most all of the young generation have their own smartphones and this led to almost all of the young generation are too focused with technological advancement that they loss their interest in learning. The traditional method way of teaching the children is not interesting enough to grab the interest of children. Therefore, this is one the reason why the children are not focused in learning. In consequence, the development of this project is to tackle the problems of children losing their focus on learning plus introduce them new and advanced technology called Augmented Reality. This application will be using Unity 3D as the main software requirement in developing this project application. Besides that, this application is developed to evaluate the user acceptance of augmented reality to learn English alphabets. Thus, with this the application will be available in android phone where android is more popular and easily obtained. Furthermore, not only the application can be educational its also consist gamification-based module. Additionally, this application will grasp the interest of the children where they can learn and have fun at the same time. Apart from that, this application is free to use. Finally, the goal of this project is to help the children in learning English alphabets.
A Temporal Knowledge Graph Application for Network Security of Power Monitoring System Based on KNN and SVM

Static knowledge graphs applied to power monitoring systems can no longer guarantee network security in the current situation, so it is necessary to develop dynamic, time-scale knowledge graphs in the current context. This paper proposes a temporal knowledge graph application based on KNN and SVM. Curves with multiple K-values are used in the KNN model to determine feature importance and filter data noise, and a supervised learning classification SVM approach is used to predict four-dimensional data. The ultimate goal is to generate multiple temporal knowledge graphs and use them in a power monitoring system to ensure network security.
PROCEDURE FOR USING NEURAL NETWORKS FOR SEGMENTATION OF RASTER IMAGES

Currently, means of semantic segmentation of images, based on the use of neural networks, are increasingly used in computer systems for various purposes. Despite significant successes in this field, one of the most important unsolved problems is the task of determining the type and parameters of convolutional neural networks, which are the basis of the encoder and decoder. As a result of the research, an appropriate procedure was developed that allows the neural network encoder and decoder to be adapted to the following conditions of the segmentation problem: image size, number of color channels, permissible minimum accuracy of segmentation, permissible maximum computational complexity of segmentation, the need to label segments, the need to select several segments, the need to select deformed, displaced and rotated objects, the maximum computational complexity of learning a neural network model is permissible; admissible training period of the neural network model. The implementation of the procedure of applying neural networks for image segmentation consists in the formation of the basic mathematical support, the construction of the main blocks and the general scheme of the procedure. The developed procedure was verified experimentally on examples of semantic segmentation of images containing objects such as a car. The obtained experimental results show that the application of the proposed procedure allows, avoiding complex long-term experiments, to build a neural network model that, with a sufficiently short training period, ensures the achievement of image segmentation accuracy of about 0.8, which corresponds to the best systems of a similar purpose. It is shown that the ways of further research in the direction of improving the methodological support of neural network segmentation of raster images should be correlated with the justified use of modern modules and mechanisms in the encoder and decoder, adapted to the significant conditions of the given task. For example, the use of the ResNet module allows you to increase the depth of the neural network due to the leveling of the gradient drop effect, and the Inception module provides a reduction in the number of weighting factors and the processing of objects of different sizes.
CONDITIONS FOR THE EFFICIENCY OF PERSPECTIVE MANAGEMENT IN A HIGHER EDUCATIONAL INSTITUTION

This article discusses the issue of personal activity competence and manager's readiness for innovation, his knowledge and skills as a manager on the main provisions of the legislative and regulatory framework for innovation, the foundations of the theory and practice of pedagogical innovation and management of educational innovation.
ACTIVITIES TRANSFER PROCESS TECHNOLOGICAL DEVICES EFFICIENT USE FACTORS

This article reveals the issues related to the peculiarities of the organization of the educational process for conducting laboratory and practical classes using electronic versions in higher technical educational institutions.
STAGES OF DEVELOPMENT OF THE SYSTEM OF CONCEPTS IN THE CONDITIONS OF CREDIT EDUCATION ON THE BASIS OF THE PRINCIPLES OF MODULARITY AND NONLINEARITY

In the article, the author describes stages of development of the concepts system, based on synergetic and acmeological approaches, as well as on the allocation of generic and specific concepts in their nonlinear and modular study.