Reviewerly/exHarmony huggingface dataset:
THEORY OF SCIENCE EDUCATION BY S.I. HESSEN AND MODERN CONCEPTION OF SCIENTIFIC LITERACY

In the literature, the concept of science education by S.I. Hessen is scarcely described, but at present it deserves close attention due to a number of reasons: the need to increase the level of scientific literacy of the Russian population; the absence of a generally accepted concept of scientific literacy in Russian pedagogy; the need to distinguish between the concepts of “natural science literacy” and “scientific literacy”; lack of a reasonable model for the formation of scientific literacy in the education process. The purpose of the study is to determine the correlation between the concepts of “natural science literacy” and “scientific literacy” and to define the significance of the practical implementation of scientific education proposed by S.I. Hessen in modern conditions. The objectives of the study are to compare the modern concept of scientific literacy with the theory of science education offered by S.I. Hessen and to determine the theoretical contribution of this theory to the problem of distinguishing between the concepts of “natural science literacy” and “scientific literacy”. I compared the main provisions of the theory of science education with the concept of scientific literacy, presented in the scientific works of Norman Lederman, professor at the Illinois Institute of Technology, and with the framework documents of the international PISA study. The author revealed the similarity of the main provisions of the theory of science education developed by S.I. Hessen, and modern pragmatic concepts of scientific literacy. This conclusion allowed us to rely in our study on the philosophical and anthropological approach. The author substantiated the distinction between two types of literacy: scientific literacy and natural science literacy. The hierarchical relationship of types of literacy was revealed. The author proposed a model of the structure of scientific literacy based on five competencies.
Prediksi Tingkat Pengangguran Berdasarkan Data Time Series Menggunakan Regresi Linear (Studi Kasus : Kota Salatiga)

Unemployment is a very big problem. Coupled with the outbreak of the COVID-19 virus which resulted in many employees and workers being laid off. The purpose of this study is to predict the unemployment rate based on the number of the workforce. To produce an accurate prediction requires valid data in the long term. This makes it a reference for forecasting the unemployment population in a 5-year time series. For forecasting, a method is needed, namely the Linear Regression method. Linear regression is a statistical method that serves to test how far the relationship between the causal variables and the effect variables is. After forecasting, prediction data is generated in 2022, and the population and unemployment have changed from the previous year. Where the population in 2022 is predicted to be 144189 and the number of unemployed is 4513 people. This result is a prediction, not 100% accurate, therefore it would be better if you use another method to compare the prediction results and the level of accuracy.
Open-Set Face Identification on Few-Shot Gallery by Fine-Tuning

In this paper, we focus on addressing the openset face identification problem on a few-shot gallery by finetuning.The problem assumes a realistic scenario for face identification, where only a small number of face images is given for enrollment and any unknown identity must be rejected during identification.We observe that face recognition models pretrained on a large dataset and naively fine-tuned models perform poorly for this task.Motivated by this issue, we propose an effective fine-tuning scheme with classifier weight imprinting and exclusive BatchNorm layer tuning.For further improvement of rejection accuracy on unknown identities, we propose a novel matcher called Neighborhood Aware Cosine (NAC) that computes similarity based on neighborhood information.We validate the effectiveness of the proposed schemes thoroughly on large-scale face benchmarks across different convolutional neural network architectures.
Meningkatkan Kemampuan Mengenal Huruf dengan Menggunakan Flash Card pada Anak Sekolah Dasar di SD Negeri Wasur Merauke

Language skills are a basic need for elementary school children to be able to communicate and socialize with each other. One of the most basic language skills is recognizing letters in order to enter the reading stage. This study aims to improve the ability of students to recognize letters, spell words, and recognize pictures. The method used in this research is to use a flash card. By using flash cards, the learning method will be more creative and not monotonous so that students will be more enthusiastic in the teaching and learning process. Flash card digunakan sebagai alat bantu agar anak mampu mengenal huruf, mengeja kata dan mengenal gambar. Dalam menganalisis data, peneliti menggunakan metode observasi dan wawancara. Observation method is used to analyze the ability of students during class research. While interviews are used to determine the development of each child during the research. This research was conducted at Wasur State Elementary School. The object of this research is the 1st grade elementary school students. The reason the researcher chooses the first grade elementary school students is because the first grade elementary school students aged around 7-8 years are children who have beginner language skills. so that researchers hope that with this research, grade 1 elementary school students at Wasur State Elementary School can improve their language skills, namely letter recognition, spelling words, and recognizing pictures.
Review on interior design using augmented reality

People nowadays are very interested in new technology and its capabilities. Augmented and virtual reality are two of the most popular topics right now. The Augmented Reality merges the virtual and physical worlds. This approach will be applied to interior design in this case that enhance the view of customers. The customer is looking for a platform that combines the majority of the functions with improved visibility. In interior design, augmented reality provides the buyer with the delight of purchasing their assets. The furniture that best matches their home decor, such as the colour of a wall, etc., improves and boosts market value. This paper will look at the notion of Augmented Reality and its application. We will also know the process of overlapping virtual data in a real-time environment of a 2D or 3D virtual image.
Layer Decomposition based Local Tone Mapping Operator

Dynamic range of an image directly defines the number of levels it can accommodate in an image. In general, a dynamic range of 256 is in use. Defining dynamic range of an image need to be done by considering the display unit on which the image will be displayed on. If the dynamic range extends over 256, the dynamic range is said to be high dynamic range. This range may extend up to 10,000. This kind of images can’t be displayed on display units which can’t differentiate that many pictorial information. This kind of pictorial information need to be converted so that the regular display units can adapt the format. This must be done without losing much information. This process is very crucial and is done by several tone mapping operators. Tone mapping operators are of two types, global and local. Global tone mapping operators apply same mapping function throughout the image while the local tone mapping operators use different mapping functions for local regions of the image. Though the quality of global TMOs is better, there are many halo effects in the converted image. In this paper, a global TMO based on decomposition is proposed intended to reduce these effects. Image is decomposed in to two layers, base, and detail. A hybrid decomposition and optimization are proposed to improve the quality of converted image.
Analysis of Teacher Training Program in The Perspective of Knowledge

The main concern of National Qualification Framework is to standardize the qualification at higher level. Secondly, the teacher education comes under the domain of higher education which the NQF describes from 5-8 levels. The curriculum of B.Ed. (Hons) falls under 6th level of the framework and revised in 2010. To analyze the alignment between compulsory subjects of B.Ed. (Hons) program with the aspect of “knowledge” given in the NQF was the focus of this research. Data collection were made through Content analysis and alignment matrix. For analyzing the alignment of the compulsory courses of B.Ed. (Hons) program with the component of “knowledge”, alignment matrix was used. Three types of categories were developed i.e., aligned, partially aligned and not aligned. These three categories were assigned codes such as 1 for aligned, 2 for partially aligned and 3 for not aligned. The categories and sub-categories of “knowledge” which were simply defined with little explanation in the courses were considered as partially aligned while the detailed discussion on the sub-categories of “knowledge” in the courses was considered as fully aligned under alignment matrix. But the sub-categories not discussed at all were considered as not aligned during analysis of compulsory courses of B.Ed. (Hons) elementary program through alignment matrix.
Privacy protection methods of location services in big data

Abstract The rapid development of mobile communication technology not only brings convenience and fun to our life, but also brings a series of problems such as privacy disclosure. Therefore, it is very necessary to study the privacy protection method based on location service to strengthen the security of location privacy. The purpose of this work is to improve the security of location privacy and prevent the disclosure of user privacy by studying the characteristics of location services and privacy protection methods. This article first describes the characteristics of the important location privacy protection law, and then studies the structural characteristics and operation process of the location privacy protection law. This work evaluates the advantages and disadvantages of different methods, and finally compares the performance of several privacy protection algorithms through experimental analysis. Through the research of hiding space method, two-level cache method based on user grid, differential privacy protection method and experimental analysis of the algorithm, an effective privacy protection algorithm can be obtained. It can better protect the location privacy of users. For example, dual-active in the hidden space algorithm has the best privacy protection performance. Compared with other algorithms, the success rate of generating hidden space is increased by more than 10%, and the time of generating hidden space is shortened by about a quarter. The algorithm It has certain practical value and significance for use in the privacy protection of users.
Information Technologies in the Research Activities of Museums: from Digital Catalogs to Artificial Intelligence Methods

The article is of a historiographic nature and is intended to record the main stages in the development of hardware-software complexes and systems for creating digital images (DI) of museum storage items and their (DI) application in intra-museum activities: from solving practical problems of documenting the discovery (acquisition) of museum funds with historical artifacts, their existence in museums, conservation and restoration, creation and development of catalogues, to the implementation of historical and art history research, implemented using the methods of mathematical statistics and a wide range of modern approaches, technologies and scientific disciplines of Data Science. For the first time in Russian historiography, the expansion of the range of research tasks is considered, which has been going on from the mid-1970s to the present and has become possible, on the one hand, in connection with the growing understanding of the information potential of DI of museum objects, and on the other hand, with the digital transformation of traditional technical and technological methods of analysis of museum items, highlights the history of design and development of specialized hardware and software systems; an original periodization of the identified processes is proposed, a brief description of each of the 4 identified stages is given (including a methodological breakthrough that occurred at the turn of the 20th-21st centuries) and the results of the most significant scientific projects are described.
New approach of diagnosing sarcasm using multi action units and head movements

Sarcasm, a sharp and ironic utterance designed to cut or to cause pain, is often used to express strong emotions, such as contempt, mockery or bitterness. Sarcasm detection is of great importance in understanding people’s true sentiments and opinions. Most Existing techniques of detecting sarcasm use speech, writing text, signs as a base to catch percent of sarcasm even with limited accuracy. In this article, a new approach of detecting sarcasm using three techniques of machine learning has been proposed. Eight action units and eight head movements from Facial Action Coding System are considered as a base rule to generate effective features to train and test machine learning techniques. The selection of these units and movements are performed according the advice of some specialist psychiatrists. The simulation results view significant accuracy of diagnosing sarcasm exceed 86% which reflects the robustness of the proposed approach also open the way for further works in this field of research.
Global-View Re-identification Tracking with Transformer

Identity matching and trajectory association are the core of multi-object tracking (MOT) task. Recent works have also focused on the rich information contained in the trajectories, aiming to learn the strong connection between the long-term motion information and the inherent representation information of the target. However, in most current MOT trackers, trajectory update is sensitive. Once the detected object in the video frame is difficult to associate with the existing trajectories, the model quickly updates the target identity and the numbers of tracking trajectories. We propose a tracking framework named GRTrack based on fine-grained re-identification (ReID) feature extraction for reappeared targets in video from a global view. Our model not only preserves the long-term relationship between the global trajectory query and the tracking target motion, but also weakens the sensitivity to low-score updated trajectory. For reappeared targets in specific motion scenarios, we retain more long-term association, thus greatly improving the accuracy of identity matching. Our model performs well on the SportsMOT dataset and achieves satisfactory results.
An ML-Based Classification Scheme for Analyzing the Social Network Reviews of Yemeni People

The social network allows individuals to create public and semi-public web-based profiles to communicate with other users in the network and online interaction sources. Social media sites such as Facebook, Twitter, etc., are prime examples of the social network, which enable people to express their ideas, suggestions, views, and opinions about a particular product, service, political entity, and affairs. This research introduces an Machine Learning-based (ML-based) classification scheme for analyzing the social network reviews of Yemeni people using data mining techniques. A constructed dataset consisting of 2000 MSA and Yemeni dialects records used for training and testing purposes along with a test dataset consisting of 300 Modern Standard Arabic (MSA) and Yemeni dialects records used to demonstrate the capacity of our scheme. Four supervised machine learning algorithms were applied and a comparison was made of performance algorithms based on Accuracy, Recall, Precision and F-measure. The results show that the Support Vector Machine algorithm outperformed the others in terms of Accuracy on both training and testing datasets with 90.65% and 90.00, respectively. It is further noted that the accuracy of the selected algorithms was influenced by noisy and sarcastic opinions.
PEMBELAJARAN BAHASA INGGRIS SECARA DARING BERDASARKAN PERSEPSI SISWA Studi Kasus di SMP Anugerah Abadi Pamulang Tangerang Selatan

Online learning is learning that is carried out remotely using media such as ZOOM Meeting, Google Classroom and others. During this pandemic, online learning is a learning that must be done to avoid the spread of the covid 19 virus. In carrying out online learning, it is necessary to have a good internet signal so that it will support the smoothness of this online learning. In addition, it is also necessary for the creativity of the educators so that students remain interested in participating in online learning.&#x0D; The writing of this article is to find out and understand the implementation of online English learning during the pandemic based on student perceptions.
THE CORRELATION BETWEEN DIGITAL LITERACY AND ENGLISH PROFICIENCY OF UNIKA MUSI CHARITAS FIRST-YEAR STUDENTS

This study aimed to discover the correlation between digital literacy and English proficiency of first-year students at Unika Musi Charitas.One hundred seventy three students were involved by using purposive sampling technique.The data were collected by using questionnaire which elaborates students' digital literacy as well as the score of their English proficiency.To analyze the results, Pearson Product Moment formula was used to measure the relationship between the two discussed variables.Findings were described into the results of participants' English proficiency level, digital literacy insight as well as the correlation test.Viewing from the proficiency level, 64.2% of the participants were categorized as basic users which can perform limited language use on daily topics.In addition, the mean score of their digital literacy insight was 66.99 with the maximum and minimum scores were 100 and 10 descriptively.The correlation test obtained significant correlation between digital literacy and English proficiency with Pearson correlation value of 0.394 at significance level of 0.000.This strongly confirms that the ability of using digital things and language carry positive intercourse.
Engagement in Online Newspaper Articles Written by Female Authors

Newpaper articles demand a link between the readers and the authors. They engage their readers by presenting several convincing clauses yet objective. Furthermore, they frame the authors’ position in the text. So that the readers will follow the authors’ flow. They wrap them all in an Appraisal Framework Theory proposed by Martin and White (2005). Gender and psychological theories from Shields (2000), Coates (2016), and Guimond (2008)are considered. This study is aimed to explore the manifestation of engagement in online newspaper articles written by female authors. It employed descriptive qualitative method in the form of discourse study analysis. It analyzed eight articles taken from three wellknown newspaper websites. The findings revealed that the eighth authors mostly employed heterogloss clauses. Female authors mostly use disclaim clauses. There was 47,9% of the whole clauses indicate disclaim. Meanwhile, clauses or utterances which indicate personal/internal subjectivity (author’s opinions) or entertain were 22,5%. Clauses that indicate external subjectivity or entertain were 21,1%. The fewest distribution was proclaim clauses which were only 8,5%. This study contributes in English teaching learning. Since it helps beginner writers to engage the link between readers and authors by presented clauses and utterances. Keywords: Engagement, Newspaper, Articles, Female, Authors
How is mathematics applied to real world problems?

Applied mathematics is the application of mathematics to real world problems.It is an incredibly useful field with a wide range of applications from biological and social sciences to computer animation and finance.Professor Anotida Madzvamuse is a professor of mathematical and computational biology whose work includes data-driven mathematical modelling, mathematical analysis of models, parameter estimation and model selection by fitting models to Mathematics is essential to our way of life.It is used all around us, from weather forecasting, engineering and finance to modelling how diseases spread.
A Novel Hybrid Quantum Particle Swarm Optimization With Marine Predators for Engineering Design Problems

The computational efficiency of the quantum particle swarm optimization (QPSO) is significantly higher than that of the traditional particle swarm optimization when solving the parameters of the optimization problem model. However, the exploration and exploitation abilities of the QPSO are weak, based on the historical best position and the global best position. Enlightened by the multi-stage search strategies of marine predators algorithm, we propose a novel hybrid quantum particle swarm optimization algorithm with marine predators (HMPQPSO) in this paper. The evolutionary process of the algorithm is divided two stages: firstly, the Brownian motion of the predator is introduced to the exploration. The randomness and uniformity of which can expand the solution space of particles; secondly, the Levy motion strategy and dynamic parameter strategy are used to update the position, which can accelerate the convergence of the algorithm and enhance the diversity of the algorithm. Meanwhile, both fish aggregation devices(FADs) and opposition-based learning strategy incorporated are used to increase the diversity of the population and prevent the phenomenon of premature particle aggregation. The algorithm is applied to distinct types of CEC2017 benchmark test functions and four multidimensional nonlinear structure design optimization problems, as compared to other recent algorithms. The results demonstrate that the convergence speed and accuracy of HMPQPSO are notably superior to that of other algorithms.
Kemampuan Menulis Paragraf Persuasif Siswa Kelas VIII SMP Negeri 6 Binjai

This study aims to determine the ability to write persuasive paragraphs in class VIII SMP Negeri 6 Binjai. The research method used in this research is descriptive method. The research sample was carried out at random (random sampling) so that the sample was obtained, namely class VIII-1, which consisted of 40 students. Based on the data obtained, it can be seen that the Ability to Write Persuasive Paragraphs of Class VIII Students of SMP Negeri 6 Binjai with the average score obtained is 72. Thus, it can be seen that students of class VIII SMP Negeri 6 Binjai are quite capable of writing persuasive paragraphs, this can seen from the average value obtained by these students.
Teaching Vocabulary Using Word Wall Media

The purpose of this study was to determine the effectiveness of learning vocabulary using word wall media for seventh grade students of SMP Negeri Selangit in the 2018/2019 Academic Year. This research method is pre-experimental with one group pre-test and post-test design. The results showed that there were four main findings, namely the student’s scores on the pre-test 51.25, the student's scores on the post-test 70.53. The normality in the pre-test was 3,200 and 11,070, while the post-test results showed 5,427 and 11,070 and the result of the paired t-test calculation was 11.14. In conclusion, learning vocabulary using word wall media is significantly effective in class VII students of SMP Negeri Selangit in the 2018/2019 Academic Year.&#x0D; Keywords: Teaching, Vocabulary, Word Wall Media