Reviewerly/exHarmony huggingface dataset:
THE IMPACT OF USING YOUTUBE SOCIAL MEDIA ON STUDENTS' POSITIVE BEHAVIOR IN INDONESIAN LANGUAGE CLASS V AT SD INPRES BONTOMANAI

This type of research is quantitative research with a one-group pre-test-post-test design. The sample and population are fifth-grade students at SD Inpres Bontomanai, totaling 25 students. The instruments used to collect data were pretest, posttest, and positive behavior questionnaires of students. The data analysis technique used is descriptive analysis technique and inferential analysis technique. The results of this study are the average post-test results of 79.44. based on the results of hypothesis testing using the one-sample t-test, a significance value of p(sig.(2.Tailed) is 0.000 because p &lt;0.05 then H0 is rejected and H1 is accepted. It can be said that there is an influence of social media youtube on students' positive behavior in the subject of Indonesian language class V SD Inpres Bontomanai
ESSENTIAL CHARACTERISTICS OF SCIENTIFIC RESEARCH ACTIVITIES OF STUDENTS OF HIGHER EDUCATION INSTITUTIONS

Modern specialists of any professional field should be distinguished by professional competence, the ability to update knowledge as well as process a significant amount of information, and creatively solve professional tasks. The specified qualities are formed in the process of professional training in the institutions of higher education, in particular through the participation of students in scientific and research activities. The purpose of the article is to investigate the essential characteristics of scientific research activities of students of higher education institutions. Research methods: analysis of scientific literature, systematization (to clarify key research concepts), generalization (for the purpose of forming author's conclusions). As a result of a comprehensive study of the problem, the essential characteristics of the scientific research activity of students were clarified, by which we understand the practice of obtaining new scientifically based knowledge, aimed at a purposeful change of social reality, which is implemented in a logical sequence through the application of appropriate forms and methods of scientific knowledge. The most important features of the students' scientific research activity have been determined: in its essence, it is an empirical activity; it is purposeful and characterized by the interconnection of certain elements, procedures and methods; is built within the framework of logical and constructive schemes, methods and means of cognition, characteristic of scientific and research activity; performed according to the research algorithm; is based on facts that require empirical verification; the result of research work is new knowledge about objects; is a methodological regulation that sets a logical direction for the selection of methods and means of activity. It is substantiated that scientific research activity is implemented at three levels (reflective-theoretical, experimental-theoretical and research), each of which involves a step-by-step process (problem definition; hypothesis formulation; selection of research methods and tools; implementation of the research plan; evaluation of the obtained results) and application of appropriate research methods. Research tasks at these levels are aimed at the study and scientific analysis of a real practical situation. The structure of students' scientific research activity involves a set of elements: motives, goals, object and subject of research, process and result.
MENINGKATKAN KEMAMPUAN LITERASI NUMERASI DENGAN MODEL PEMBELAJARAN PJBL SISWA KELAS V SDN 01 TAMAN KOTA MADIUN

Nowdays, one of the Government's focuses is on developing students' literacy and numeracy skills. The purpose of this study is to improve students' numeracy literacy skills by implementing the Project Based Learning (PjBL) learning model in the mathematics subject, sub-section of data presentation. The type of this research is Classroom Action Research (CAR). The research subjects were 27 students fifth grade students at SDN 01 Taman Kota Madiun, consisting of 12 male students and 15 female students. The data collection technique used is observation and testing. The results of observations during the Mid-Even Semester Assessment, as many as 15 students (56%) did not reach the KKM, and received low scores on essay questions. The average value obtained is 59.50. After the implementation of Project Based Learning (PjBL), in Cycle I the number of students who did not reach the KKM decreased to 10 students (37%) and the average test score obtained was 73.80. In Cycle II the number of students who did not reach the KKM decreased to 7 students (26%) and the average test score obtained was 81.78. From the results of research conducted by applying the Project Based Learning (PjBL) learning model, it can improve the numeracy literacy skills in presenting data for class V students at SDN 01 Taman Kota Madiun.
Information Bounds and Convergence Rates for Side-Channel Security Evaluators

Current side-channel evaluation methodologies exhibit a gap between inefficient tools offering strong theoretical guarantees and efficient tools only offering heuristic (sometimes case-specific) guarantees. Profiled attacks based on the empirical leakage distribution correspond to the first category. Bronchain et al. showed at Crypto 2019 that they allow bounding the worst-case security level of an implementation, but the bounds become loose as the leakage dimensionality increases. Template attacks and machine learning models are examples of the second category. In view of the increasing popularity of such parametric tools in the literature, a natural question is whether the information they can extract can be bounded.In this paper, we first show that a metric conjectured to be useful for this purpose, the hypothetical information, does not offer such a general bound. It only does when the assumptions exploited by a parametric model match the true leakage distribution. We therefore introduce a new metric, the training information, that provides the guarantees that were conjectured for the hypothetical information for practically-relevant models. We next initiate a study of the convergence rates of profiled side-channel distinguishers which clarifies, to the best of our knowledge for the first time, the parameters that influence the complexity of a profiling. On the one hand, the latter has practical consequences for evaluators as it can guide them in choosing the appropriate modeling tool depending on the implementation (e.g., protected or not) and contexts (e.g., granting them access to the countermeasures’ randomness or not). It also allows anticipating the amount of measurements needed to guarantee a sufficient model quality. On the other hand, our results connect and exhibit differences between side-channel analysis and statistical learning theory.
Experimental entanglement generation using multiport beam splitters

Abstract Multipartite entanglement plays a central role in optical quantum technologies. One way to entangle two photons is to prepare them in orthogonal internal states, for example, in two polarisations, and then send them through a balanced beam splitter. Post-selecting on the cases where there is one photon in each output port results in a maximally entangled state. This idea can be extended to schemes for the post-selected generation of larger entangled states. Typically, switching between different types of entangled states requires different arrangements of beam splitters and so a new experimental setup. Here, we demonstrate a simple and versatile scheme to generate different types of genuine tripartite entangled states with only one experimental setup. We send three photons through a three-port splitter and vary their internal states before post-selecting on certain output distributions. This results in the generation of tripartite W, G and GHZ states. We obtain fidelities of up to <?CDATA $(87.3\pm 1.1)\%$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mo stretchy="false">(</mml:mo> <mml:mn>87.3</mml:mn> <mml:mo>±</mml:mo> <mml:mn>1.1</mml:mn> <mml:mo stretchy="false">)</mml:mo> <mml:mi mathvariant="normal">%</mml:mi> </mml:math> with regard to the respective ideal states, confirming a successful generation of genuine tripartite entanglement.
A Study of Hybridized Smell Agent Symbiotic Organism Search in Congress on Evolutionary Computation Functions

This paper presents a study of the Smell Agent Symbiotic Organism Search (SASOS) hybrid algorithm. SASOS is developed from bioinspired Smell Agent-Based Optimization(SAO) and Symbiosis Organism Search (SOS) algorithms. Bioinspired algorithms often lack a balance between speed and accuracy to achieve optimal performance efficiency and a global search for the best solution. To address these challenges, the algorithm reduces the imbalance between diversification and intensification in bioinspired algorithms to improve the search for global optima. SASOS performance was evaluated in sixteen selected Congress on Evolutionary Computation (CEC) functions using Aggregative Best Counts (ABC) compared to the regular SAO and SOS algorithms. For an advanced performance comparison, the convergence study was carried out on each CEC function to assess the fitness of the algorithms based on the Desirable Convergence Goal (DCG). Evaluation results using 50 iterations have shown that SASOS performed better withABCof56.25%than the SAO and SOS algorithms with ABC of 28.12% and 15.63%, respectively, in standard benchmark functions. Furthermore, in the convergence study, 1000 iterations were superimposed for each algorithm on the CEC functions. The convergence results showed that SASOS obtained the best DCG of 58.83%compared to SOS and SAO with DCG of 25.00% and 16.67%, respectively. These results made the performance of the hybrid SASOS uniquely different from other similar approaches.This is because the hybrid SASOS satisfactorily balanced the diversification and intensification phases in the bioinspired SAO and SOS algorithms. The eligible characteristics of the hybrid SASOS with respect to ABC and DCG showed its compatibilityand significance forvarious engineering optimizationapplications
Penerapan e-book berbasis socio-scientific issues dalam meningkatkan kemandirian belajar pada materi sistem sirkulasi darah

Independent learning is an important aspect for students to learn without being accompanied by a teacher (learning outside the classroom). The purpose of this study was to determine the effectiveness of e-books based on socio-scientific issues (SSI) in increasing students’ learning independence on the material of the blood circulation system. The research method used is a quantitative method, with a nonequivalent control group design. The sample in this study were two class XI in one high school in Yogyakarta, each class amounted to 33 students. The instrument used is a learning independence questionnaire, with reference to 5 aspects of learning independence. Hypothesis testing was carried out with the help of SPSS using the Mann Whitney U test. In addition, data analysis techniques were also carried out using the n-gain score. The results of hypothesis testing regarding learning independence using the Mann-Whittney U test showed that there was a significant difference in the average value of learning independence between the experimental class and the control class. Then, the average gain score for students’ learning independence in the experimental class was 0.64 which was included in the medium category. While the average in the control class is 0.27 in the low category. It can be concluded that the use of SSI-based e-book media is effective in increasing students’ learning independence on the material of the blood circulation system.
INCREASING LESSON EFFICIENCY WITH THE USE OF DIGITAL TECHNOLOGIES IN THE EDUCATIONAL PROCESS

This article describes multimedia digital learning, a software development program, an animation material preparation schedule, multimedia training, and a two-way simulator for students.
Data Migration from Relational to NoSQL Database: Review and Comparative Study

New storage requirements, analysis, and visualization of Big Data, which includes structured, semi-structured, and unstructured data, have caused the developers in the past decade to begin preferring Big Data databases, such as NoSQL, that comes to overcome the boundaries of relational Databases such as unlimited scalability, high performance, data modeling, data distribution, and continuous availability. Due to those benefits ensured by this new technology, quite recently, considerable attention has been paid to data migration from relational Database to NoSQL Database. So, in this context, the purpose of this paper is to provide a comparative study of some recent approaches proposed by various researchers to migrate data from relational to NoSQL databases, as well as discussing and analyzing the results of those proposed techniques. This research allowed us to gain a basic understanding of the contributions and approaches that have already been made, as well as the benefits and limits of each proposal.
Efficient Algorithms for Large Prime Characteristic Fields and Their Application to Bilinear Pairings

We propose a novel approach that generalizes interleaved modular multiplication algorithms for the computation of sums of products over large prime fields. This operation has widespread use and is at the core of many cryptographic applications. The method reformulates the widely used lazy reduction technique, crucially avoiding the need for storage and computation of “double-precision” operations. Moreover, it can be easily adapted to the different methods that exist to compute modular multiplication, producing algorithms that are significantly more efficient and memory-friendly. We showcase the performance of the proposed approach in the computation of multiplication over an extension field Fpk , and demonstrate its impact with record-breaking implementations of bilinear pairings. Specifically, we accomplish a full optimal ate pairing computation over the popular BLS12-381 curve, designed for the 128-bit security level, in under half a millisecond on a 3.2GHz Intel Coffee Lake processor, which is about 1.40× faster than the state-of-the-art. Similarly, we perform the same computation over the BLS24-509 curve, targeting the 192-bit security level, in ~ 2.6 milliseconds, achieving a speedup of more than 1.30x. We also report a significant impact on other applications, including protocols based on supersingular isogenies.
Generating Better Items for Cognitive Assessments Using Large Language Models

Writing high-quality test questions (items) is critical to building educational measures but has traditionally also been a time-consuming process. One promising avenue for alleviating this is automated item generation, whereby methods from artificial intelligence (AI) are used to generate new items with minimal human intervention. Researchers have explored using large language models (LLMs) to generate new items with equivalent psychometric properties to human-written ones. But can LLMs generate items with \textit{improved} psychometric properties, even when existing items have poor validity evidence? We investigate this using items from a natural language inference (NLI) dataset. We develop a novel prompting strategy based on selecting items with both the best and worst properties to use in the prompt and use GPT-3 to generate new NLI items. We find that the GPT-3 items show improved psychometric properties in many cases, whilst also possessing good content, convergent and discriminant validity evidence. Collectively, our results demonstrate the potential of employing LLMs to ease the item development process and suggest that the careful use of prompting may allow for iterative improvement of item quality.
MANAGEMENT OF PROFESSIONAL DEVELOPMENT OF TEACHERS IN AN INSTITUTION OF GENERAL SECONDARY EDUCATION

The study is devoted to the issue of psychological and pedagogical science and educational practice – the professional development of teachers. The state of development in scientific sources on the issue of professional development and self-development of teachers, management of professional development of teachers is analyzed, and the necessity of forming their acmesynergistic position is substantiated. The purpose of the study ‒ to find out the ability of teachers for professional self-development and to develop a program for optimizing their professional development in a general secondary education institution as a basis for the formation of an acmesynergistic position. I Nikishin's method “A teacher's ability to creative self-development” and the questionnaire “What is your creative potential” (according to L.Karamushka) were used to identify teachers' ability for professional self-development. А program for optimizing the professional development of teachers, based on the analysis of scientific literature and the results of a diagnostic study, has been developed, which focuses on their ability to professional self-development and the formation of an acmesynergistic position, and the ways of its implementation in an institution of general secondary education have been outlined. The program is aimed at creating conditions for personal and professional growth in the institution of general secondary education and provides for the following areas of activity; assistance to teachers in identifying mental resources; assistance in mastering methods of self-diagnosis, methods and methods of professional self-improvement; technologies for changing personal traits and developing professionally significant qualities; development of the ability to overcome professional difficulties, increase the level of competence, as well as stimulation and motivation of teachers for professional self-development. The role of acmeological and coaching technologies in the formation of the acmesynergistic position of the teacher is revealed, which is focused on: self-knowledge and self-development of the teacher's personality; actualization and support of his personal and professional growth and self-development; transformation of the inner world, changes in the intellectual, emotional and behavioural spheres of the individual; focusing on the highest professional achievements.
Artificial intelligence is the key to success in practical application

Artificial intelligence technology is rapidly advancing year by year, and thus the possibilities of using artificial intelligence in every branch of science. The importance of artificial intelligence and its components has been known for a long time. They are seen as tools and techniques that make the world a better place With their simple and everyday techniques, they make the world a mistake-free place. These technologies and applications are not only related to our general and everyday life, but also affect and have significance for other domains as well. The paper will analyze the application of artificial intelligence and its influence today.
Exploring the Benefits of Reinforcement Learning for Autonomous Drone Navigation and Control

&lt;p&gt;This is research about how reinforcement learning benefits autonomous drone navigation and control&lt;/p&gt;
A comprehensive study on need of cyber security

Cyber Security plays a huge role in the current field of information technology. With security of the information becoming one of the biggest problems in the world. When we think about the cyber security the first thought that comes to our mind is ‘cyber crimes’ which are greatly rising day by day. Various Private companies and Governments are taking necessary actions to stop these cyber-crimes. Besides various measures cyber-crimes are still a big concern for everyone. This paper’s main motive is to show various challenges faced by cyber security around the world and most used technologies. It also sheds light on latest cyber security techniques, ethics, measures and the trends of cyber security.
Error-state Kalman Filtering with Linearized State Constraints

&lt;p&gt;In recent years, the error-state Kalman filter (ErKF) has been extensively employed across various applications, including but not limited to robotics, aerospace, and localization. However, incorporating constraints into the ErKF framework when state constraint is necessary has remained a challenging task due to its intrinsic properties. This paper explores all possible ways to achieve this goal in the context of the estimate projection method. In particular, the constraint can be enforced before or after the ErKF's correction step. We approach the problem from a mathematical perspective by deriving analytical solutions and discussing their statistical properties. We prove that the two mentioned methods are statistically identical for a linear system with linear constraints. Conversely, the filter's behavior remains uncertain in the presence of linearized constraints. However, we provide a special case of the nonlinear constraint, wherein the results of the linear case remain valid. To support our theorem and verify the filter's performance when the assumptions are invalidated, we present two Monte Carlo simulations under the increasing initialization error and the constraint's incompleteness. The simulation results clearly confirm our insights and lead to the conclusion that constraining the error-state after the correction may offer superior outcomes compared to its competitor.&lt;/p&gt;
Marine Vessel Detection in Sea Fog Environment Based on SSD

Aiming at solving the problem of low marine vessel detection accuracy in the sea fog environment, a deep learning-based anti-fog marine vessel detection method is proposed in this paper by combining defogging preprocessing with marine vessel detection model. Firstly, gated context aggregation network (GCANet) network is used to process the marine vessel image. Then, the processed image is sent to a modified SSD network, wherein anchors are tuned by statistical characteristics of the shape of marine vessel to detect the position of the marine vessel. Furthermore, to alleviate the loss of feature information due to defogging processing, channel attention mechanism based on the squeeze and excitation module (SE) is added to base convolutional layer of SSD. The comprehensive experiments and comparison results show that the proposed G-SEMSSD network is more suitable for marine vessel detection under sea fog environment.
PICTURES AS LEARNING – TEACHING AID IN IMPROVING ENGLISH VOCABULARY AT ELEMENTARY SCHOOL IN DENPASAR

It has been researched in some studies and related theories confirming that using picture in teaching English vocabulary was very effective. Especially for young learner in elementary school which has Bahasa Indonesia as their main language, the vocabulary problem used to occurred in spelling, pronunciation, grammatical use, and meaning. Those language aspects become main obstacle for them. This research explores the implementation of English vocabulary and to find out the score improvement in using picture in learning process. The objective of this research is to find out the effectiveness of picture in improving students’ vocabulary. The research is conducted in Santo Yoseph 1 elementary school Denpasar in the class of 3B .It was conducted in two cycles to twenty-seven participants. Instruments used were tests, questionnaires, and observation. Results showed that an initial vocabulary mastery was 75.6 points, and increased to 86.08 in the final cycle of the study. In the same way, the questionnaire results in the second cycle revealed that although the students still found English learning (85.50) and memorizing vocabulary (70.37%) difficult, their interest in learning it increased (59.26% from 29.63%). Finally, the observation results of the second cycle also showed the improvement of both students’ and teacher’s teaching and learning atmosphere as well as interest. However, a further study and learning policy are worthy to assure the application of the pictorial aids facilitating the attractive and motivating learning atmosphere in the future.&#x0D; Keywords: Secondary student, vocabulary, pictorial aid