Reviewerly/exHarmony huggingface dataset:
BENEFITS FROM ONLINE LEARNING: EMPIRICAL ASPECT

The spread of COVID-19 has led to the closure of educational institutions all over the world. During on the pandemic period, students could take classes from any location, provided they have access to a computer. Students in online classes can working together with each others from various places to share any different opinions and cooperate to solve the problems. Many students have reported positive experiences with online courses. The most valuable benefits for online learning were: flexibility (time &amp; place); ability to view/review lecture videos as necessary; lower spent fund for parking and food as well; didn’t have to deal with other students, who was disturbing class; didn’t have to wait for other students who work at a slower pace. Students prefer more passive strategies online, such as re-reading or taking notes, instead of engaging in the more effortful retrieval practice. Research has demonstrated the benefits of retrieval practice (taking quizzes) on long-term retention (the so-called testing effect) and end-of-course outcomes. As an increased amount of learning is happening online, it is important that we promote effective learning strategies within these environments. Students who took all or partly of their class online performed better, on average. The main research question was: how Ukrainian students evaluate online learning? The study was held Ukrainian city – L’viv. Ukrainians were in age from 15 till 46 (with M = 18,9, S.D. = 2,5). The main bulk of respondents studying at Lviv Polytechnic National University. Research was anonymous, and was carried out from 16-th till 23-th of March 2022. In total 411 respondents took part in the research. Questioner measuring benefits from online learning was constructed for the investigational needs. Students from L’viv positive evaluated quality and comfort from online learning. They liked to have lectures, trainings and seminars online. The most popular benefits from online learning were: combine learning with other things, more free time, saving money, more time for sleeping. Online learning improved the level of technical skills the participants.
PERFORMANCE ANALYSIS OF HECTOR SLAM AND GMAPPING FOR NAVIGATION FOR MOBILE ROBOT NAVIGATION

One of the most significant elements of a moving robot is mapping. The robot's capacity to identify its surroundings and translate them into a map allows it to navigate effectively from one spot to another while avoiding impediments that may arise during the navigation process. The SLAM method already has a mapping capability, so it can continuously localize the position against the map. In this experiment, 2D laser scanning data was obtained using RPlidar-A1 and then processed by the slam algorithm, namely gmapping and hector mapping to produce an occupancy grid map. The map is displayed by the RViz visualization widget, and its length is measured using the RViz measurement tools. The results of the occupancy grid map generated by the gmapping algorithm with a laser scan matcher have a lot of noise, and lose orientation. At the measured point length, the gmapping algorithm has slightly more error. The hector mapping algorithm has better performance than gmapping with a laser scan matcher on the RPLidar-A1 device.
Research on the teaching innovation model of the integration of information technology and music education

In the environment of intelligent education, in order to comprehensively improve the quality of music education, we should adhere to the application advantages of information technology as the basis, by reconstructing the form of music education, optimizing the music teaching process, and enriching the music teaching materials, so that students can better understand music Teaching content, to achieve the essential innovation of music education model. Through the analysis of the current problems in music education, combined with the interpretation of the advantages of the integration of information technology and music education, a teaching innovation model of the integration of information technology and music education is proposed.
DAMPAK PEMBANGUNAN SARANA DAN PRASARANA TERHADAP PENINGKATAN KUALITAS PROSES BELAJAR SISWA DI SMA KRISTEN KETAPANG 1 JAKARTA

Presentation of data on the impact of building facilities and infrastructure on the quality of student learning at SMA Kristen Ketapang1 Jakarta. To obtain data using quantitative methods as many as 110 people, with a population of six classes divided into MIPA and IPS majors. A sample of 10% is taken from the specified population. By using the purposive sampling method, 11 students attended the Ketapang 1 Jakarta Christian School from KB-TK to SMA. Data acquisition techniques are carried out through observation, surveys, and documentation. The product-moment correlation equation was used to analyze the data. From the research output it is accepted that the hypothesis (Ha) uses the interpretation that the impact of infrastructure development and infrastructure on the quality of the student learning process at SMA Kristen Ketapang1 Jakarta is classified as high using a coefficient interval of 0.629 more than the "r" table of 0.602. Based on the output of the Hypothesis Test (Ha), it can be concluded that there is a significant influence between the impacts of infrastructure development &amp; infrastructure on the quality of the student learning process at the Christian High School Ketapang 1 Jakarta.
Application of the ontological approach to the design of automated systems in education

At present, the need to consolidate, formalize and reuse the accumulated knowledge of specialists in various fields, including in the field of education, as well as to improve its quality, is becoming more and more urgent. The problem of the quality of training is central in the aspect of the demand for specialists. Knowledge as one of the components of intellectual potential is used both in the innovation system and in the educational process. At the modern level of development of information technologies in the tasks of education, automated systems are widely used, which greatly facilitate the learning process. However, the automated systems used have one significant drawback associated with the limited possibilities for further development and use of the specialist knowledge formed in them. The problem of increasing the efficiency of the design and development of automated systems in education is solved by developing a method for representing a specialist knowledge model based on an ontological approach. The purpose of this work is to develop an ontological representation of the components of the knowledge model of a specialist in the field of education.
White blood cell image classification using deep learning method

White blood cells play an important role in the field of diagnosis of major blood related diseases. Our body contains mainly the three types of blood cells, which include red blood cells, white blood cells (WBCs), and platelets. WBCs are also called immune cells because they are the cells of the immune system. Identification of blood-related diseases are mainly based on the characteristics or the properties of the white blood cell's nucleus. So the reliable classification of white blood cells is important and increasingly demanded. Insufficient data is one of the limitation in the existing methods. Also unwanted background elements in the dataset reduced the classification performance. So that to classify the blood cell images, an enhanced method using convolutional neural network approach is proposed. The LISC database is used for the classification of the white blood cells. LISC is a public database which contain five classes of blood cell images. Some classes contain less number of images, so certain data augmentation techniques like flipping, rotation, shearing etc are applied. The augmented dataset contains irrelevant background along with white blood cells, so that the proposed method introduced a segmentation technique to remove the irrelevant portions. The images with unwanted background elements leads to low noise to signal ratio and which affect the classification performance. In this paper proposed a DenseNet architecture, which is trained to differentiate among five different classes of white blood cells. The performance of the system is evaluated based on the Accuracy, Precision and Recall achieved. Experimental results demonstrate that the proposed model can achieve better classification performance than traditional CNN. The best DNN model, DenseNet-201 yields an accuracy of 97.79%.
THE DEGREE TO WHICH TEACHERS OF THE NORTHERN GOVERNORATES IN PALESTINE PRACTICE DISTANCE LEARNING FROM THEIR POINT OF VIEW AND ITS OBSTACLES

The study aimed to identify the degree to which the teachers of the northern governorates in Palestine practice distance learning from their point of view and its obstacles. The two researchers used the descriptive analytical approach, and the study sample consisted of (328) teachers who work in government schools in the directorates of the northern governorates in Palestine, which numbered (18) directorates, who were selected in a stratified random manner, and the study applied to them a questionnaire whose validity and reliability were verified by appropriate statistical methods. The results of the study showed that the degree of distance learning practice was medium, as the arithmetic mean of the total degree was (2.7), and it also showed that the degree of distance learning obstacles was medium, with an arithmetic mean of the total degree (3.39). In light of these results, the study came out with several recommendations, including the necessity of conducting special courses for teachers to train them on how to design computerized programs and employ open learning resources.
System Contol by Hand Gestures using Artificial Intelligence

Information era" is what we call the present world and there are many advancements in every field across the globe, especially in the field of AI computer vision. Researchers have found interesting results experimenting upon the fields which has lead to creation of many other interesting fields such as object detection, object tracking, image processing and more. Here in our project keeping "Vision Based Human Detection Techniques: A descriptive review", by Shahriar Shakir Sumit, Dayang rohaya among Rambli and Seyedali Mirjalili as the base paper, were implementing a project of hand tracking and gesture recognition to combine AI with computer vision to achieve complete control over computer without the use of Keyboard or mouse. The project involves simple and predefined gestures which is recognized by AI via camera in the computer and performs tasks accordingly. This project can be helpful to keep a wide step ahead to overcome the increasing problem of e-waste as the project completely eliminates the use of keyboards and mouse resulting in less production and hence less e- waste
Keterampilan Menulis Teks Eksposisi Siswa Menggunakan Metode Think Pair and Share

The purpose of this study was to determine the effect of the think pair and share method on the exposition of the writing skills of class X SMKN 3 Payakumbuh students. This research method is a quantitative study using the experimental method. The results showed that the mean score of students in the experimental class was 78.37, while in the control class it was 70.62. In conclusion, the think pair and share method affects the writing skills of the exposition text in the experimental class. There is a significant difference in the results of text writing skills using the think pair and share method and conventional methods.&#x0D; Keywords: Expositional Text Writing Skills, Think Pair and Share
An Evaluation of the Challenges of Mainstreaming Cybersecurity Laws and Privacy Protection in Nigeria

The goal of this study is to discuss cybercrimes and review cybersecurity threats, with a focus on cybersecurity legislations in Nigeria that seek to protect the privacy and digital property of the Nigerian people and the country’s institutions. The study’s methodology includes a qualitative examination of Nigeria's present national cybersecurity laws. It explores how effective they are and interrogates the additional measures that may be needed-notably in cybersecurity and related national laws-to ensure that individuals, institutions are protected and that society and the national economy function well in the 21st Century. Individuals have a right to privacy, so do companies and various other institutions in post- modern societies. This right varies widely across different countries across the globe. In some countries it is minimal or non-existent, in others it is hard fought for constitutional right. In order to reap the benefits of advanced technologies in the information age, personal and institutional data have to be made available to merchants, institutions and government. The benefits of advanced technologies are immense-and vital to modern economies. However, this process involves risks. Abuse of the data is a risk, and criminal abuse has become widespread.
Efficient Decision Trees for Multi-class Support Vector Machines Using Large Centroid Distance Grouping

We propose a new technique for support vector machines (SVMs) in tree structures for multiclass classification.For each tree node, we select an appropriate binary classifier using data class centroids and their in-between distances, categorize the training examples into positive and negative groups of classes and train a new classifier.The proposed technique is fast-trained and can classify an output class data with a complexity between O(log 2 N ) and O(N ) where N is the number of classes.The 10-fold cross-validation experimental results show that the performance of our methods is comparable to that of traditional techniques and required less decision times.Our proposed technique is suitable for problems with a large number of classes due to its advantages of requiring less training time and computational complexity.
VIDEOCONFERENCING FOR CONTINUING PROFESSIONAL EDUCATION OF ENGINEERING STUDENTS: EVALUATING THE FEEDBACK

Currently, we observe a wide use of distance learning technologies at different levels of education, including higher education. The need for safe indirect interaction between teachers and students during the COVID-19 pandemic became the impetus for the widespread implementing and mass “testing” of such technologies. Various types of distance technologies and learning formats are still widely employed, which makes it relevant to search for the ways of their effective usage. The research aims to identify the advantages and disadvantages of using videoconferencing within the system of continuing professional education for engineering students. The tasks of the research are to define the basic concepts of videoconferencing as a tool of pedagogical interaction, as well as to identify, analyze and generalize its advantages and disadvantages based on a survey conducted among students and teachers. The results show generally positive attitude of the respondents to videoconferencing and their readiness to use this format in education process. The findings can help overcome a number of shortcomings of videoconferencing, increase its efficiency and adopt this format in the future.
The Reform Strategy of College Chinese Teaching Mode in the Big Data Era

In the new educational environment, the basic and instrumental functional advantages of college Chinese are gradually prominent. Doing Chinese teaching well not only helps to enrich students' Chinese knowledge reserve, but also to improve students' Chinese learning cognition and cultivate students' Chinese accomplishment. In the environment of big data era, we should face up to the realistic problems existing in the current Chinese teaching, through optimizing the teaching mode, rearranging the teaching lines, reconstructing the college Chinese teaching mode based on the big data platform, improving the quality of Chinese teaching. Based on the background of big data era and the practical problems in college Chinese teaching, this paper puts forward some concrete reform strategies.
Prototyping Circular Materials Based on Reprogrammable Matter

For almost two centuries, design, manufacturing and consumption models have exploited Earth’s valuable resources (elements, minerals, flora and fauna) on a profound scale. As resources become depleted, there is a desperate need to develop new approaches for how materials are utilised and fabricated with to reduce or even reverse waste and pollution. The research aims to create a new design and fabrication process that can develop circular materials, which contributes to a circular economy. The research presented documents initial prototyping explorations that build towards a vision of physical products/structures composed of reprogrammable matter. Meaning, an object’s properties (shape, colour, texture) can be updated by uploading information from design tools into matter to avoid redundancies and heal damage. The research is presented as a pictorial in the format of an annotated portfolio that combines photographs and videos to communicate the research-through design process along with our findings and insights.
USING DUOLINGO APPS TO IMPROVE ENGLISH READING COMPREHENSION OF ENGINEERING STUDENTS IN UNIVERSITAS BORNEO TARAKAN

Learning English is matter of learning language components and language skills. Reading is the most difficult learning that plays important role in mastering English Language. Learning reading is quite challenging. It needs various techniques and applications. The transformation of English language learning is mostly affected by technological advances. The development of English Language Teaching (ELT) resources, Duolingo participates to transform method of English language learning on smartphone. The aim of this study is to find out the impact of Duolingo in ELT as extensive learning. Pre-experimental design with pre-test and post-test was used in this research. The researcher involved 15 students as sample with 2 months practicing duolingo apps with 20 xp on each day intensity of practice. The researcher used reading tests as pre-test and post-test and questionnaire to see students’ perception. According to the results, there was massive improvement on students score. Students also felt that Duolingo is useful apps to use everyday to learn English.
The Implementation of School Literature Movement in Senior High School

The school literacy movement is a government-sponsored initiative aimed at improving Indonesia's reading culture and educational quality.The goal of this article is to offer an overview of the implementation of the school literacy movement in senior high schools.The approach of literature review was used.This study material was gathered from a number of sources, including libraries and internet websites that house dictionaries, books, journals, periodicals, encyclopedias, and other publications.In this study, documentation was employed as a data gathering approach.This study's findings try to illustrate how the school literacy movement has been implemented in high school.
Purwarupa Sistem Pemantauan dan Pengendalian Pertumbuhan Tanaman Cabai dalam Screen House

Chili (Capsicum annuum L.) is a well-known spice plant and is loved because of its distinctive spicy taste. In addition, chili also contains good nutrients including vitamins A, B, C, E, potassium, phosphorus, calcium, folate, antioxidants, protein, and anti-cancer substances. Chili cultivation provides good economic potential because market demand is stable and even increases in certain seasons. One of the chili planting methods is by using a screen house which allows farmers to better control various growth parameters. In this study, an IoT-based monitoring and control system for chili plant growth parameters was developed using a Raspberry Pi, sensors, and other electronic devices. Growth parameter data is processed and sent to an online server and then presented with a time series-based visualization.
The Role of Sensory Gardens in Autistic Children

The purpose of this study is to examine the impact of therapeutic or sensory gardens in the behavioral and learning aspects of children with autistic disabilities. To understand the same, a total of 30 students between the age group of 4 to 10 were examined from an autism school in Tirunelveli, Tamilnadu. The study was conducted through observational analysis and structured interviews with doctors, caregivers, and teachers of the school. The result shows that sensory gardens have a considerable impact on autistic children as it helps them in improving their communication skills and positive behavioral changes. The study also shows that the sensory gardens enhance the learning focus in autistic children and the guidelines based on the same have been formulated.
Correction to: ANNPRO: A Desktop Module for Automatic Segmentation and Transcription

In an older version of this paper, there were errors in the affiliations of three authors, Katarzyna Klessa, Brygida Sawicka-Stępińska and Hanna Kasperek. Three authors were incorrectly affiliated with the Institute of Romance Studies. This has been corrected to the Faculty of Modern Languages and Literatures.
English Translation Intelligent Recognition System based on Automatic Generation Algorithm

In order to improve the automation level of English translation system software and the accuracy of English machine translation, the optimization design of English automatic translation system is carried out, and the English translation intelligent recognition system using autonomous generation algorithm is proposed. Information system product design mainly includes machine translation algorithm design and software design. Through semantic feature analysis and sentence compilation combination method, English autonomous compilation algorithm optimization product design is realized, and English autonomous compilation information system product design is realized in embedded environment. The application software system includes vocabulary collection template, data processing module, word scheduling template and automatic control template. The intelligent product design of compilation management system is realized through cross compilation and multi-threaded statement compilation and loading.
Facial Emotion Detection using Convolutional Neural Network

Non-verbal specialized strategies, e.g.look, eye development, and motions are utilized in numerous uses of human-PC connection, among them facial feeling is generally utilized as it conveys the enthusiastic states and sensations of people.In the machine learning calculation, a few significant separated highlights are utilized for displaying the face.As a result, it won't get a high accuracy rate for acknowledging that the highlights rely on prior knowledge.Convolutional Neural Network (CNN) has created this work for acknowledgment of facial feeling appearance.Looks assume an essential part in nonverbal correspondence which shows up because of the inner sensations of an individual that thinks about the countenances.This paper has utilized the calculation to distinguish features of a face such as eyes, nose, etc.This paper identified feelings from the mouth, and eyes.This paper will be proposed as a viable method for distinguishing outrage, hatred, disdain, dread, bliss, misery, and shock.These are the seven feelings from the frontfacing facial picture of people.The final result gives us an accuracy of 63% on the CNN model and 85% on the ResNet Model.