Reviewerly/exHarmony huggingface dataset:
Visual Imagery Strategy In Enchance Students’ Reading Comprehension

The objective of the research were to find out whether or not the use of Visual Imagery Strategy can enhance the students’ reading comprehension at the Eighthof MTs Pondok Pesantren Al-Urwatul Wutsqa Benteng.This research employed a quantitative method that applied one class. The population of this research was the eighth grade students in academic year 2019-2020. There were 253 students spread in eighth classes (VIII.A, VIII.B,VIII.C, VIII.D, VIII.E, VIII.F, VIII.G, and VIII.H) and each class consist appropriately 27-37 students. The researcher took simple random and chose VIII.C as the representative and the number of total sample is 23 students.The data of the research were collected by using one kinds of instruments, namely reading comprehension test. Reading test was used to obtain data of the students’ reading comprehension ability in Reading Comprehension by using visual Imagery strategy.The result of data analysis showed that there was significant difference between the students’ score after they were taught by using Visual Imagery Strategy and before they were taught by Visual Imagery Strategy. It was proved by the mean score of the post-test which was higher than the mean score of pre-test (62.04&gt;53.86). Furthermore, the result of the p-value (0.004) was lower than level of significant (α = 0.05); which means that H1 was accepted. Based on data analysis, the research concluded that: the use of Visual Imagery Strategy effective in improves students’ reading comprehension.
Autonomous Learning in Higher Education Students: A Systematic Review of The Literature On Wos Between 2019-2022

In higher education, autonomous learning is the capacity that students develop from the combination of a series of affective, social, cognitive and metacognitive factors that allow students to self-regulate their learning. In this context, the present study aims to systematize the evidence from the scientific literature in relation to autonomous learning in higher education students. The PRISMA 2020 method was used for the phase of identification of records in the WoS (Web of Science) database during the period 2019-2022, which allowed the identification of 8,339 studies, and from the application of data exclusion criteria, 13 were selected. studies whose purpose was to answer the research question: What skills do higher education students use to develop autonomy in their learning? The data was systematized based on the authors, countries of publication according to the origin of the journal, keywords, dimensions, instruments used, application strategies and conclusions of the studies to analyze possible patterns, similarities and characteristics that can be contrasted with others. studies to identify possible strengths or weaknesses regarding autonomous learning in higher education students. The results show that Spanish journals lead in content on the subject. Likewise, there is a wide variety of keywords such as: higher education, academic self-regulation, learning strategies, etc. In addition, 84.6% of the studies used questionnaires for the development of their research. It is concluded that, according to the content of the studies, it is important to highlight that the use of ICT and teaching support are important to promote the self-regulation of the learning of university students, as well as to highlight that, through pedagogical mediation, Through counseling, tutorials and teaching support, it facilitates the development of planning skills, concentration, motivation and reflection on the learning of higher education students.
Minimal linear codes derived from weakly regular bent and plateaued functions

The construction of (minimal) linear codes from functions has received much attention in the literature. In this paper, we derive several minimal codes from the sets of pre-images of weakly regular plateaued and bent functions over the odd characteristic finite fields. Based on the recent construction method, we obtain six-weight and seven-weight minimal codes from these functions. The Hamming weights in proposed codes are calculated from the character sums of the sets based on the Walsh spectrum of the employed functions, while the weight distributions of the codes are determined from both the sizes of the employed sets and the Walsh distributions of the employed functions.
Integrating extensive and intensive reading worksheets on digital platforms

This study aims at exploring the strengths of extensive reading and intensive reading (EXIT) integration by involving the use of digital-platform base worksheet in optimizing the students’ reading skill. The foci include revealing the students’ perspectives towards such a hybrid implementation as well as theoretical justifications to the significances of EXIT integration and digital-platform base worksheet in reading activities. This descriptive qualitative study took place in a state university in North Sumatera ad involved 30 students of English education taking Writing class. Questionnaire, interview, and documentation were used to collect the data. The qualitative data were then analyzed to meet triangulation data validity. It was found that the students perceive the significances of EXIT integration and roles of digital-platform base worksheet are oriented to optimize their reading comprehension. Documentation also showed the students’ interests and motivation in EXIT using digital-platform base improved. Exploration to teachers’ perspectives towards the same treatment is suggested to see the significances of each reading technique and reading tool from different point of view.
Working from Home: Creativity and Innovation in the High-Tech Industry in Israel

Creativity is a crucial aspect of tech management, as it allows hi-tech workers to identify and solve problems, generate new ideas, and create innovative solutions that meet the needs and desires of consumers. The COVID-19 pandemic has had a significant impact on the way that people work, with many companies shifting to remote work as a means of maintaining business continuity. This shift has led to a debate about the impact of remote work on creativity, with some arguing that working from home increases creativity since it allows for more flexibility and autonomy. In contrast, others say it decreases it since it can lead to isolation and a lack of collaboration. While some evidence suggests that working from home may positively impact creativity, there is also evidence to suggest that it may have a negative impact. The main objective of this study is to investigate differences, if any, in the perceived creativity among hi-tech workers working from home or the office. The study provides a more nuanced understanding of hi-tech workers' attitudes toward creativity, innovation, and related risk-related issues.&#x0D; We used a validated questionary about the extent of innovation and creativity of people in general. Then we investigated these characteristics with the extent of working from home or the office. We statistically compared the means of variables of interest for categories of interest of respondents.&#x0D; We found no significant difference between high-tech workers working from home or the office. Yet, we discovered that hi-tech workers working from home reveal more resilience toward creative ways to solve problems even though these ways are associated with more risk. They are willing to take more risks to accomplish assignments innovatively and creatively. We also found that managers and development hi-tech workers tend to work from home.
Fintech

The financial world is getting a digital makeover. Traditional banks are set to disappear in a decade. Digital payments are the norm making the world a cashless and a more inclusive society. Crypto, the digital currency, was originally conceived to replace the centralized financial system but is ending up as a haven for speculators and illegitimate players. Through AI, high-frequency trading has taken over 90% of global securities trading.
Faculty of Applied &amp; Creative Arts, Universiti Malaysia Sarawak

The advent of globalised connectivity has intricately linked local communities with worldwide information dissemination, forming a global consciousness among individuals. This essay explores the interplay between globalised connectivity and the “risk society,” analyzing its impact on democracy. Through cases such as Cambridge Analytica, the Arab Spring, and the ICIJ, it reveals the dual nature of globalised connectivity, fostering democratic advancement while compromising data privacy. The essay underscores the need for active democratic participation while managing associated risks. As society navigates this transformative phase, harnessing globalised connectivity’s potential to amplify voices and ensure accountability is crucial for a balanced future of enhanced global democracy and personal information security.
WORKING IN THE DIGITAL EDUCATIONAL ENVIRONMENT: PROS AND CONS

Using the capabilities of the digital educational environment for students is one of the key forms of obtaining quality education and self-realization, and for teachers – a way to improve their professional skills in creating interesting classes and developing methodological materials. With the help of digital environment, a teacher can work effectively online, prepare interactive classes for students on various online platforms, improve their pedagogical skills by participating in competitions, webinars, conferences and trainings. Students can view classes online, use various resources for online learning, create projects using modern educational technologies and engage in self-education. However, working in the digital educational environment has many risks and dangers that can significantly worsen a person's emotional state and lead to material losses.
THE ERASMUS+ FUNDED KNOWLO PROJECT DIGITALIZATION ON A GLOBAL CONTEXT IN EDUCATION A TEACHER’S PERSPECTIVE

This paper reflects the works being carried out under the Erasmus+ funded on-going KNOWLO project, Promoting knowledge-sharing culture in Learning Organization, Project number: &amp; Code 2021-1-LV01-KA220-VET-000029991KA220-VET-Cooperation partnerships in vocational education and training. The project is aimed to cater an essential support to any vocational or traditional Higher Education Institution (HEI), which is looking forward for a change or transforming to become Smart learning organization. The project is ongoing and schedule to finish by December 2023, The KNOWLO project has 5 results that project partners from 4 difference countries are committed to develop they are arranged in the order as Result number 1 to Result number 5. This particular paper discusses about the Result number 1, Sub-criteria identified or the development of Transformational Framework (Digitalization of Learning Practices) on a Global context. This paper can be treated as a case study towards identifying various aspects of consideration when undergoing transformation from traditional learning organization to Smart learning organization. The paper discusses the perspective from the point of view of one of the crucial stakeholders in the educational sector (Teachers). This paper puts forth what is the perspective of teachers towards smart learning organization and what aspects they assume are necessary to involve all the stake holders towards such a transformation. The paper highlights the current situation in context with digital transformation from the teacher’s perspective and the results collected highlight how teachers from different regions view digital learning practices on with different aspects and needs. The data collected has been analyzed on a qualitative &amp; quantitative pattern and the final discussions put forth a guide of do’s &amp; don’t, for any learning organization looking forward for a transformation into smart learning organization from the teacher’s perspective.
A Study on the Characteristics of Immersive Spatial Representation in teamLab’s Media Art

This study analyzed the media art space of teamLab based on Mihaly Csikszentmihalyi's immersion theory to find out the expressive characteristics of the media experience space and cognitive thinking. As a method of the study, the teamLab's works were first analyzed focusing on the characteristics derived from the consideration of immersion theory to interpret the relationship between the expressive elements of the media art space and the immersive characteristics according to spatial expression. As a result of the analysis, teamLab's works create new artistic experiences through the fusion of natural elements and media art, and various natural elements are organically harmonized within the work and induce various visual experiences through imaginary images to the audience. In addition, the spatial and spatial changes and distortion of boundaries of the work obscure the boundaries between the audience's reality and the work, causing new sensory experiences and participation. Through the study, the relationship between the characteristics of space and the expression elements that occur in the stage of immersion in teamLab's media art space was identified, and the possibility of multiple directions and organic expressions on the boundaries of perception expressed by virtual images that induce visual interaction. Research findings indicate that the immersive characteristics of media art prioritize the dissolution of boundaries and the formation of active communication within artworks. The fusion of nature and media art stimulates audience interest and provides fluid meaning, thereby creating immersive experiences.
A Study on Teachers’ Perceptions of Gifted Education Directions with Experience in Gifted Education

Currently, the interest and demand for gifted education in Korea is decreasing, and it is analyzed that the operational stability and characterization of gifted education institutions are insufficient. In addition, there is a lack of systematic support according to the level and characteristics of individual giftedness, and the negative perception that education is a minority elite still exists. This means that although it has been 20 years since gifted education was introduced in earnest in Korea, problems ranging from the selection of gifted students to the operation of gifted education programs have not yet been resolved. Therefore, this study examines the direction of change in the definition of gifted and gifted education recipients that have been discussed so far, and based on the 1st to 5th Comprehensive Plan for Gifted and Talented Education Promotion, the current status of gifted education in Korea and its achievements and analyzed its limitations. The perception of the future direction of gifted education was examined through focus group interviews with teachers who have experience in gifted education among graduate students at K University and who are interested in gifted education. As a result of the study, three keywords were identified: selection of gifted students, education program for gifted students, and teacher education, and the details are as follows. First, as a result of discussing the selection of gifted children, there was an opinion that various measurement tools were needed, such as considering the environment of students. In addition, there was an opinion that giftedness should not be limited to intellectual ability, but that students who show outstanding talent or achievement in various fields should be provided with opportunities to receive gifted education. Second, in the gifted education program, the need for customized classes was raised by arranging the children selected for gifted education as individuals or in small groups. In addition, it was confirmed that support such as mentor system and education program was needed in cooperation with external organizations such as the Office of Education. Third, teacher education in charge of gifted and talented education often lacks expertise in the field, so it was discussed that gifted and talented teachers need to have that expertise, and it was confirmed that additional research on teacher education is needed.
IMPLEMENTATION OF DATA MINING MODELS WITH ALGORITHMS K-NEAREST NEIGHBOR IN MONITORING THE NUTRITIONAL STATUS OF CHILDREN AND STUNTING

Information systems are needed in the development of children in the developmental period and especially in the world of health. Monitoring of children's nutritional status and stunting is necessary to determine children's weight and meet the criteria for children's nutritional status. Pukesmas Muara Satu, North Aceh District, is an implementing element or assistant to the duties of Poskesdes and Midwives in the Health of children's nutritional status and stunting in Paloh Punti Village, which is one of the agencies under the Ministry of Health. This study aims to monitor the growth and development of children such as measuring weight, height, measured to detect early if unwanted things occur such as malnutrition. The problem in this study is designing and monitoring an Information system for child nutritional status and stunting that is integrated with a web application. The purpose of this study is to find out staff and employees in managing, monitoring and accessing data. So that the data at the puskesmas is recorded in the system, and can quickly determine data on the nutritional status of children and stunting. The results of this study are to be able to find out an information system that is able to reduce problems that occur in managing data on the nutritional status of children and stunting at the Muara Satu Health Center. This system is very important because it can make it easier for staff to record the nutritional status of children and stunting at the Health Center. then the results of the KNN (K-Nearest Neighbor) model classification with the recapitulation of the value of new cases with old cases in the first test section is 0.6944, the second test is 0.6388, the third test is 0.555, the fifth test is 0.6388.
Hyper-Parameters Activation on Machine Learning Algorithms to Improve the Recognition of Human Activities with IoT Sensor Dataset

Objectives: To enhance the accuracy of the Human Activity Recognition (HAR) in the computer vision. The study aims to explore the practical applications of HAR in various fields, including gaming, rehabilitation, health monitoring, human-robot interaction, sports, video surveillance, and robotics. The specific objective is to develop a system that can accurately recognize and categorize the human actions thereby enabling the design and implementation of effective human-computer interaction systems. Methods: In this research, a HAR module is developed to extract relevant features such as Accelerometer, Gyroscope and Magnetometer features from signals obtained from IoT wearable sensors. 7352 samples are considered. Machine learning models such as K-Nearest Neighbor Algorithm (KNN), Random Forest Algorithm (RF), Naive Bayes Algorithm (NB), Decision Tree Algorithm (DT), Multi-Layer Perceptron (MLP) Algorithm and Proposed Algorithm (MLP classifier with adam optimizer and relu activation) are employed to automatically recognize and classify activities performed by individuals based on the raw data. The models are trained and evaluated using statistical parameters, including accuracy score, precision, recall, and f1-score. A comparison is made between existing approaches such as KNN, RF, NB, DT and MLP Algorithms and the proposed model to assess its performance. Findings: The study reveals that the proposed model MLP classifier with adam optimizer and relu activation is effective in recognizing and categorizing the human activities with 95% of accuracy. The statistical evaluation metrices demonstrates the reliability and robustness of the proposed model with 96% of precision. Novelty: This research contributes to the field of Human Activity Recognition by presenting a novel approach that combines the IoT wearable sensors, feature extraction, and machine learning models to accurately recognize and classify human actions. The proposed model outperforms the existing methods in terms of accuracy. The study highlights the importance of the proposed algorithm and its potential for improving the human computer interaction systems. Keywords: Classification; Human Activity; IOT; Machine Learning; Supervised Learning
The Effect of Crossword Puzzles on Learners' Vocabulary Development in EFL Context

Vocabulary mastery plays an important role in learning English. The teacher's role is very important in helping students achieve their goals because acquiring a sufficient number of words is a fundamental requirement for English proficiency. This drives this study to investigate the effectiveness of the usage of crossword puzzles to enhance vocabulary mastery. This study was conducted at SMP Annur Assalafy Pasuruan. This study was conducted in a design of experiments, a semi-empirical study using quantitative techniques. The sample used in this study included students from class 7 of SMP Annur Assalafy Pasuruan, with a total of 36 students in the two classes. Class 7A is the control class and Class 7B is the experimental class. The instrument used in this survey is a multiple-choice question with up to 20 test items. The records series strategies used in this study have been pre-test, treatment, and post-test. The results of this study show that the use of crossword puzzles effectively improves students' vocabulary. According to the SPSS calculation results, the scores obtained in the experimental classes after treatment are higher than those obtained before treatment. Therefore, from the hypothesis test, the value of Sig is 0.00, which is &lt;0.00. 0.05, so H0 is not accepted and Ha is accepted. This means that media crosswords puzzle influence English vocabulary (Y). As a result, crossword puzzle affect the increase in English vocabulary proficiency among 7th-grade students of SMP Annur Assalafy Pasuruan.
An Adaptive Interactive Multiple-Model Algorithm Based on End-to-End Learning

The interactive multiple-model (IMM) is a popular choice for target tracking. However, to design transition probability matrices (TPMs) for IMMs is a considerable challenge with less prior knowledge, and the TPM is one of the fundamental factors influencing IMM performance. IMMs with inaccurate TPMs can make it difficult to monitor target maneuvers and bring poor tracking results. To address this challenge, we propose an adaptive IMM algorithm based on end-to-end learning. In our method, the neural network is utilized to estimate TPMs in real-time based on partial parameters of IMM in each time step, resulting in a generalized recurrent neural network. Through end-to-end learning in the tracking task, the dataset cost of the proposed algorithm is smaller and the generalizability is stronger. Simulation and automatic dependent surveillance-broadcast tracking experiment results show that the proposed algorithm has better tracking accuracy and robustness with less prior knowledge.