Reviewerly/exHarmony huggingface dataset:
THE EFFECTIVENESS OF USING YOUTUBE AS MEDIA IN TEACHING SPEAKING AT MAN 4 KEDIRI

Using YouTube as media is one of the ways to teach speaking. Using YouTube as media help students to be better independent English speaker and makes the students easier in learning English. The main purpose of the study is to examine the effectiveness of using YouTube as media on students’ speaking score of the eleventh grade IIS-2. Quantitative was selected as a research approach, whereas the research design used was Quasi Experimental by using posttest-only design. This research used two classes which became experimental and control group. The experimental group was taught speaking using YouTube as media, while the control group was taught using picture as media. To collect the data, post speaking tests in experimental and control group were administered. Data were analyzed by using t-test. The findings indicated that score of the experimental group higher than the control group. Thus, it can be concluded that using YouTube as media in teaching speaking is effective.
Project Management Competencies of Educational Technology Professionals in Higher Education: A Qualitative Analysis of the Knowledge, Skills, and Abilities

The purpose of this research is to explore the competencies of project managers in the field of educational technology in the higher education context. A conceptual framework is presented based on the current definition of the field of educational technology; knowledge, skill, and ability (KSA) statements; and the sixth edition of the Project Management Body of Knowledge (PMBOK). Using this conceptual framework, an interview protocol with 11 open-ended questions was developed by the research team to gather relevant information from experienced educational technology project managers. We then interviewed N=13 educational technology project managers from institutions of higher education across the United States and analyzed these data using the Constant Comparative Method. Three dominant themes emerged during data analysis: âknowledge,â âskills,â and âabilities.â These themes are described in detail along with the properties and categories from our data, and a discussion of our findings is provided. Recommendations are made for both researchers and professionals.
PEMBUATAN PORTAL WEBSITE SEKOLAH SMA NEGERI 1 SUNGAILIAT SEBAGAI MEDIA INFORMASI

KThe existence of a school website is very important to disseminate information needed for schools, teachers, students and the community. With the website, information can be easily managed by the school. For example, important announcement information, the school operator can input the information through the website portal so that the public can read the information effectively and efficiently without having to come to school. In addition, the public can communicate with school operators through the chat feature and download the required documents via the web. Another feature is the photo album and video activities carried out by the school as a promotional media as well as the features that are connected to social networking services namely Instagram. The results of the final interview this activity was obtained that this website provides many benefits for the community as well as ease in managing information systems by operator.
The Application of Text Mining Algorithms to Discover One Topic Objects in Digital Learning Repositories

The article considers the process of digital transformation of education and the existing issues in this field. Digital technologies improve the efficiency of backend processes taking place within the unified learning platforms. The article offers possible solutions to the issue of one topic objects search in the learning repositories based on the case study of the Moscow Electronic School - a massive database of learning objects. The solution suggested in the article includes a special text mining model developed to analyze lesson script titles and a programmed algorithm aimed at extracting one topic lesson scripts and visualizing them in two-dimensional space. The efficiency of the developed model is supported by the visualization of 36,644 lesson scripts stored in the E-Library of the Moscow Electronic School.
Exploring the Influence of Blended Learning Method in English Recount Text Writing for Senior High School Students

This paper aims to explore the influence of blended learning method on the teaching of English recount text writing and examine students’ perceptions toward the implementation of the method. The design of the study was a mixed-method research designs. The data were collected by using a pre-test, post-test, and an open-ended interview. The quantitative data were analyzed using independent samples t-test, while qualitative data obtained from interviewing students were transcribed, categorized, and interpreted using interactive model analysis. The quantitative data analysis showed there was a significant effect of the blended learning method towards students' English recount text writing with a large effect size (1.03). From the interviews, it was found that the students gave positive responses to the implementation of blended learning methods in teaching writing of recount text. It can be concluded that blended learning is an effective method for teaching writing recount text for senior high school. Other researchers are expected to expand the research variable and explore this method's implementation on different English skills.
ForeSight - AI-based Smart Living Platform Approach

Abstract In the upcoming years, the internet of things (IoT) will enrich daily life. The combination of artificial intelligence (AI) and highly interoperable systems will bring contextsensitive multi-domain services to reality. This paper describes a concept for an AI-based smart living platform with open- HAB, a smart home middleware, andWeb of Things (WoT) as key components of our approach. The platform concept considers different stakeholders, i.e. the housing industry, service providers, and tenants. These activities are part of the Fore- Sight project, an AI-driven, context-sensitive smart living platform.
A Novel Classified Ledger Framework for Data Flow Protection in AIoT Networks

The edge computing node plays an important role in the evolution of the artificial intelligence-empowered Internet of things (AIoTs) that converge sensing, communication, and computing to enhance wireless ubiquitous connectivity, data acquisition, and analysis capabilities. With full connectivity, the issue of data security in the new cloud-edge-terminal network hierarchy of AIoTs comes to the fore, for which blockchain technology is considered as a potential solution. Nevertheless, existing schemes cannot be applied to the resource-constrained and heterogeneous IoTs. In this paper, we consider the blockchain design for the AIoTs and propose a novel classified ledger framework based on lightweight blockchain (CLF-LB) that separates and stores data rights at the source and enables a thorough data flow protection in the open and heterogeneous network environment of AIoT. In particular, CLF-LB divides the network into five functional layers for optimal adaptation to AIoTs applications, wherein an intelligent collaboration mechanism is also proposed to enhance the across-layer operation. Unlike traditional full-function blockchain models, our framework includes novel technical modules, such as block regenesis, iterative reinforcement of proof-of-work, and efficient chain uploading via the system-on-chip system, which are carefully designed to fit the cloud-edge-terminal hierarchy in AIoTs networks. Comprehensive experimental results are provided to validate the advantages of the proposed CLF-LB, showing its potentials to address the secrecy issues of data storage and sharing in AIoTs networks.
CROWDFUNDING SMART CONTRACT: SECURITY AND CHALLENGES

Distributed ledger-based technology crowdfunding is an appealing method for e-economy and its revolutionary concept enable improved credibility and confidentiality in transaction.It has a unique data security concept, which provides immutability, traceability, increased trust and faster settlement.An interesting use case of distributed ledger is the conventional crowdfunding.In the recent years, the acceptance of blockchain for commercial and businesses has significantly increased.Some of the industries, where the blockchain method can be applied are food supply chain, healthcare, crowdfunding, and government services.In this paper, the crowdfunding use case is chosen to be reviewed.Nonetheless, the conventional approach of crowdfunding has a few downsides, which drive away genuine investors into a legitimate business.To date, crowdfunding i.e., monetary funding is typically unregulated, and a lack of end-to-end monitoring system has led to many fraudulent projects.In addition, the traditional crowdfunding lacks transparency and proper agreement (contract) for investors.This paper aims to survey the security issues and challenges of crowdfunding and highlighted the benefits of using blockchain for such use case.
Francese e italiano, lingue della moda: scambi linguistici e viaggi di parole nel XX secolo

The French and Italian lexicon of the 20th century fashion illustrates the fashion of the time, its attitudes and feelings. In this contribution, the analysis of some cases highlights unexpected linguistic paths, which find the French matrix for reverse-loan words to Italian and vice versa, for internationalism, calques and loans. The reasons and modalities of the French linguistic influence on Italian language are investigated so as the influence that both languages receive from English language in this domain. The distribution of these language contacts can be different following two directions: the terminology corresponding to production (dresses, accessories, manufacts etc.) and terminology of fashion marketing and communication (how to communicate and promote these products in the fashion world). These two contexts bring out different lexical tendencies into the French and Italian lexicon of the 20th century.
Research on path planning of multi-rotor UAV based on improved artificial potential field method

UAV needs sensor to fly in an environment with obstacles. However, UAV may not be able to move forward when it encounters a large obstacle, or UAV will be in a dangerous state when the sensor fails briefly which disturbed by the environment factors. In order to solve these problems, the following methods are proposed in this paper. Aiming at the first problem, this paper proposes an improved APF method for path planning, and verified by simulation experiments that this method can find the optimal path. Aiming at the second problem, this paper proposes a solution to expand the range of obstacles and dynamically change the distance in the APF repulsion function. It is verified that the UAV can fly safely within the short time of the sensor problem by simulation experiments. In conclusion, this paper has an important reference value for the application of UAV online dynamic path planning in engineering.
Property Rental Price Prediction Using the Extreme Gradient Boosting Algorithm

Online marketplace in the field of property renting like Airbnb is growing. Many property owners have begun renting out their properties to fulfil this demand. Determining a fair price for both property owners and tourists is a challenge. Therefore, this study aims to create a software that can create a prediction model for property rent price. Variable that will be used for this study is listing feature, neighbourhood, review, date and host information. Prediction model is created based on the dataset given by the user and processed with Extreme Gradient Boosting algorithm which then will be stored in the system. The result of this study is expected to create prediction models for property rent price for property owners and tourists consideration when considering to rent a property. In conclusion, Extreme Gradient Boosting algorithm is able to create property rental price prediction with the average of RMSE of 10.86 or 13.30%.
On peculiarities of teaching linear algebra to future IT specialists within the program "Education in english" of the national aviation university

The article is devoted to the analysis of the practice of teaching linear algebra in English to Ukrainian and foreign students at the National Aviation University.Formulation of problem.When teaching mathematical disciplines in multinational groups, teachers face the problem of teaching educational material to students from different countries for which English is not a native language.The purpose of this study is to investigate the specifics of the project approach for teaching of certain sections of linear algebra, in particular, for the distance learning during quarantine, in English-speaking academic groups. Materials and methods. The study of effectiveness of different methods of presentation of teaching material and organization of theeducational process on lectures, practical classes, individual students' work is conducted by traditional methods, that is, by comparing the current and semester grades for different academic groups, interviewing teachers and analyzing the subjective students' assessments obtained through questionnaires.Results.Teaching mathematical disciplines, in particular linear algebra, in multinational English-speaking academic groups requires modification of standard methods and approaches.As experiment, elements of the project approach were introduced.In particular, when teaching certain issues of linear algebra in practical classes in some specialties, teachers proposed to divide academic group into several international teams for joint considered problem solving and mutual verification of results.Conclusions.Application of project approach based on the formation of international teams to solve problems in practical classes on linear algebra in English-speaking groups helps to improve students' mastering of education material.Considered approach increases interest of students and improves their performance.The use of this approach in the teaching of other mathematical disciplines gives some encouraging results.
PENGEMBANGAN BAHAN AJAR AKUNTANSI UNTUK MENINGKATKAN KUALITAS PEMBELAJARAN DI KELAS

This study aims to develop accounting teaching materials and to see the feasibility of teaching materials in improving the quality of classroom learning on the subject matter of the accounting cycle of service companies. This research is a development research adapted from the ADDIE model. There are 5 stages, namely: 1. Analysis (Analysis), 2. Design (Design), 3. Development (Development), 4. Implementation (Implementation), 5. Evaluation (Evaluation). Validation was carried out by material experts, media experts and assessments from class X accounting students of Ar-Rahman Medan Private Vocational School. Based on the assessment of material 1 on the feasibility of teaching materials for accounting books, the average score is 3.87 with the "Eligible" category, and the material expert orders 2 obtained an average score of 4.20 in the "Eligible" category, an indication of media experts is obtained on average. amounting to 4.00 in the "Eligible" category. Students' assumptions about accounting book teaching materials show an average of 4.45 with the category "Very Appropriate". Thus, the teaching material for the Accounting Service Company Cycle book is declared "Feasible" to be used as an accounting learning medium in improving the quality of learning.
Application and Analysis of Random Forest Algorithm for Estimating Lawn Grass Lengths in Robotic Lawn Mower

This paper states an estimation method for lawn grass lengths or ground conditions based on random forest algorithm from the observation data obtained by fusion of sensors.This estimation relates to Digital Twin and Virtual Twin of Hybrid Twin approach for the autonomous driving of robotic lawn mowers.The robotic lawn mowers are becoming popular with the advent of efficient sensors and embedded systems and we are now developing a practical autonomous driving and its group control algorithm for large lawn grass areas.However, one of the important functions of robotic lawn mower, that is, the length of lawn grasses or such ground conditions as dirt, gravel, or concrete, etc., are not recognized precisely with the current robotic lawn mower.As a result, the motor for cutting lawn grasses is running with constant rotation speed from the beginning to the end of operation of robotic lawn mower.This leads to the waste of battery and gives a large drawback for the control of robotic lawn mower.In order to precisely control the rotation speed of motor and save the battery, the lawn grass lengths and ground conditions are estimated by using the effective sensor data.The application of random forest algorithm to the fusion of sensors on a commercial robotic lawn mower attained more than 90% correct estimation ratio in several experiments on actual lawn grass areas.Now, the suggested algorithm and the fusion of sensors are evaluated against wide range of lawn and grounds.
<b>intRinsic</b>: An <i>R</i> Package for Model-Based Estimation of the Intrinsic Dimension of a Dataset

This article illustrates intRinsic, an R package that implements novel state-of-the-art likelihood-based estimators of the intrinsic dimension of a dataset, an essential quantity for most dimensionality reduction techniques. In order to make these novel estimators easily accessible, the package contains a small number of high-level functions that rely on a broader set of efficient, low-level routines. Generally speaking, intRinsic encompasses models that fall into two categories: homogeneous and heterogeneous intrinsic dimension estimators. The first category contains the two nearest neighbors estimator, a method derived from the distributional properties of the ratios of the distances between each data point and its first two closest neighbors. The functions dedicated to this method carry out inference under both the frequentist and Bayesian frameworks. In the second category, we find the heterogeneous intrinsic dimension algorithm, a Bayesian mixture model for which an efficient Gibbs sampler is implemented. After presenting the theoretical background, we demonstrate the performance of the models on simulated datasets. This way, we can facilitate the exposition by immediately assessing the validity of the results. Then, we employ the package to study the intrinsic dimension of the Alon dataset, obtained from a famous microarray experiment. Finally, we show how the estimation of homogeneous and heterogeneous intrinsic dimensions allows us to gain valuable insights into the topological structure of a dataset.
Penggunaan multimedia interaktif untuk meningkatkan literasi digital siswa SMP pada mata pelajaran IPA

This research using interactive multimedia to improve digital literacy of Junior High School students in natural science learning, focused in the material structure of the earth and disasters. The study consisted of two meetings using innovative technology in the form of interactive multimedia with different sub-material, namely (1) earth and volcanic structures, and (2) earth natural disasters and disaster mitigation. The aspects of digital literacy will be assessed in this research such as: accessing, analyzing and evaluating, creating, reflecting, and communicating. This research is qualitative research with descriptive method. Samples were taken with simple random sampling technique. Samples were student of grade VIII in 2 Junior High School in Bandung as many as 30 students. The result showed that natural science learning on the material structure of the earth and disasters by using interactive multimedia can improve digital literacy of Junior High School students with a difference overall percentage of 4.00 % from 1st meeting (70.33 %) to 2nd meeting (74.33 %). Thus, it can be concluded that by using interactive multimedia can improve digital literacy of Junior High School students in the material structure of the earth and disasters. At the end, it is expected to do a similar study related to the effort to improve digital literacy with other material.
SPECIFICS OF THE ORGANIZATION OF PROJECT ACTIVITIES OF STUDENTS IN VARIOUS TRAINING SYSTEMS

Хитрова Анна Викторовна
The use of social-networking sites in English language education: An exploratory study using SWOT analysis technique

The global importance of English as the language of international communication needs no description. English has gained competitive edge and is considered a requirement in order to make progress in the global world. There is bulk of research dedicated to finding better means of learning and teaching English language. The current research aims at exploring the potential of using social networking sites for improving English language skills especially in the skill areas of reading and writing. The research proposes to analyze the opinion of the participants by using SWOT analysis technique. This techniques dissects the themes from the data under strength, weakness, opportunity and threat in order to draw the picture of the potential of anything, In the current research, SWOT analysis technique was used to organize the data in the themes mentioned here. The study concludes that the use of social networking sites in English language education has marvelous potential as the students learn with ease of mind. The language is learnt in without any affective filters like anxiety or lack of motivation. Though social media sites can be effective platforms, their use may also distract the language learners with all their misinformation, ungrammatical content, and artificial human interaction. The study implicates that there is need to formulate effective strategies for proximal advantage of the strengths and countering the weaknesses and threats in order to make the best of the opportunities provided by social media sites in English language education.
ENSEMBLE META CLASSIFIER WITH SAMPLING AND FEATURE SELECTION FOR DATA WITH IMBALANCE MULTICLASS PROBLEM

Ensemble learning by combining several single classifiers or another ensemble classifier is one of the procedures to solve the imbalance problem in multiclass data. However, this approach still faces the question of how the ensemble methods obtain their higher performance. In this paper, an investigation was carried out on the design of the meta classifier ensemble with sampling and feature selection for multiclass imbalanced data. The specific objectives were: 1) to improve the ensemble classifier through data-level approach (sampling and feature selection); 2) to perform experiments on sampling, feature selection, and ensemble classifier model; and 3 ) to evaluate t he performance of the ensemble classifier. To fulfil the objectives, a preliminary data collection of Malaysian plantsâ€™ leaf images was prepared and experimented, and the results were compared. The ensemble design was also tested with three other high imbalance ratio benchmark data. It was found that the design using sampling, feature selection, and ensemble classifier method via AdaboostM1 with random forest (also an ensemble classifier) provided improved performance throughout the investigation. The result of this study is important to the on-going problem of multiclass imbalance where specific structure and its performance can be improved in terms of processing time and accuracy.
DFOGraph

With the magnitude of graph-structured data continually increasing, graph processing systems that can scale-out and scale-up are needed to handle extreme-scale datasets. While existing distributed out-of-core solutions have made it possible, they suffer from limited performance due to excessive I/O and communication costs.