Reviewerly/exHarmony huggingface dataset:
PENGEMBANGAN PROTOTYPE TRAFFIC LIGHT MIKROKONTROLER BERBASIS RDUINO MEGA PADA MATA PELAJARAN TEKNIK PEMROGRAMAN MIKROPROSESOR DAN MIKROKONTROLER DI SMK NEGERI 1 PERCUT SEI TUAN

Abstract The purpose of this research is to develop a Prototype Traffic Light Microcontroller based on Arduino Mega. This research was conducted in class XI TAV SMK Negeri 1 Percut Sei Tuan. This development research uses the Borg and Gall research model adapted from Sugiyono. Product data is in the form of qualitative data obtained from suggestions from media experts and practitioners and in the form of qualitative data from media experts and practitioners. The results of the study are: (1) Making the Prototype Traffic Light learning media the steps include making the product design developed, collecting supporting materials, finishing, protootype assessment by media experts and practitioners, product revision. (2) The results of the feasibility of the Ttraffic Light Prototype are as follows: the assessment of the Prototype by the media obtained a score of 90.25% in the very feasible category, the Prototype assessment by the practitioner obtained a score of 93.5% with the very feasible category. (3) The results of the eligibility of the Job Sheet Prototype by the practitioner obtained a chord of 92% in the very feasible category. Key Words: Development of traffic light prototype, Arduino mega, R&amp;D AbstrakPenelitian ini bertujuan untuk mengembangkan Prototype Traffic Light Mikrokontroler berbasis Arduino Mega. Penelitian ini dilakukan di kelas XI TAV SMK Negeri 1 Percut Sei Tuan. Penelitian pengembangan ini menggunakan model penelitian Borg and Gall yang diadaptasi dari Sugiyono. Data produk berupa data kualitatif yang didapat dari saran dari ahli media dan praktisi serta berupa data kualitatif yang berasal dari ahli media dan praktisi. Hasil penelitian adalah : (1) Pembuatan media pembelajaran Prototype Ttraffic Light langkah-langkah meliputi membuat desain produk yang dikembangkan, mengumpulkan bahan-bahan pendukung, Finishing, penilaian Protootype oleh ahli media dan praktisi, revisi produk. (2) Hasil kelayakan Prototype Ttraffic Light sebagai berikut : penilaian Prototype oleh media diperoleh skor 90,25% dengan kategori sangat layak, penilaian Prototype oleh praktisi diperoleh skor 93,5% dengan kategori sangat layak. (3) Hasil kelayakan Job Sheet Prototypeoleh praktisi diperoleh akor 92% dengan kategori sangat layak. Kata Kunci: Pengembangan prototype traffic light, arduino mega, R&amp;D
Materials for I. G. Frank-Kamenetsky’s biography

The article brings light to some aspects of life
Perceptual Models of Machine-Edited Text

We introduce a novel dataset of human judgments of machine-edited text and initial models of those perceptions.Six machine-editing methods ranging from character swapping to variational autoencoders are applied to collections of English-language social media text and scientific abstracts.The edits are judged in context for detectability and the extent to which they preserve the meaning of the original.Automated measures of semantic similarity and fluency are evaluated individually and combined to produce composite models of human perception.Both meaning preservation and detectability are predicted within 6% of the upper bound of human consensus labeling.
Precision-based Boosting

AdaBoost is a highly popular ensemble classification method for which many variants have been published. This paper proposes a generic refinement of all of these AdaBoost variants. Instead of assigning weights based on the total error of the base classifiers (as in AdaBoost), our method uses class-specific error rates. On instance x it assigns a higher weight to a classifier predicting label y on x, if that classifier is less likely to make a mistake when it predicts class y. Like AdaBoost, our method is guaranteed to boost weak learners into strong learners. An empirical study on AdaBoost and one of its multi-class versions, SAMME, demonstrates the superiority of our method on datasets with more than 1,000 instances as well as on datasets with more than three classes.
IMPLEMENTATION OF THE TECHNOLOGY OF FORMATION OF PEDAGOGICAL COMMUNICATIVE COMPETENCE IN FUTURE PRIMARY SCHOOL TEACHERS

The article is devoted to the study of the problem of developing the technology of formation of pedagogical communicative competence in the professional training of future primary school teachers. It is proved that one of the effective ways of its realization is modeling. It is determined that the process of technology introduction can be modeled by systematically combining three stages: target, content-activity and control-reflection. Each stage had a leading goal and was aimed at implementing specific forms of work: from designing your own communication strategy to its implementation and reflection. The model was based on the curriculum of the discipline of choice of students, aimed at comprehensive professional and communicative development.Key words: technology, communication, competence, model, stage, primary school.
RECOGNITION OF FRACTAL DIMENSION OF MEDICAL PLANT LEAVES BY USING TECHNIQUES OF IMAGE PROCESSING

The leaves of a plant having unique properties and it will be different from that of other leaves. So leaf recognition can represent a tree or plant recognition. This report describes some of the findings of currently published work in the area of leaf recognition. From these we are aiming to create a good leaf recognition system. Leaf Images acquired first goes for preprocessing. Then some relevant features are extracted. Our objective is to extract feature based on fractal dimensions. A fractal has been defined as a rough or fragmented geometric shape that can be split into parts, each of which is reduced-size copy of the whole. For classification a new learning algorithm called extreme learning machine (ELM) for single-hidden layer feed forward neural networks (SLFNs) which randomly chooses hidden nodes and analytically determines the output weights of SLFNs will be experimented using for the better result.
Realistic Horn Mod By Mc2Rok 1.35.X

Just copy and overwrite it to your favorite truck sound. Dont forget to make it twice. For interior and exterior. Have a look at video!
Aggregation for Privately Trained Different Types of Local Models

Machine learning has been a thriving topic in recent years, with many practical applications and active research aspects.In machine learning, model aggregation is an important area.The idea of model aggregation is to aggregate a global model from trained local models.However, traditional aggregation methods based on parameter averaging can not aggregate models which have different types and structures.Because parameter averaging will fail to average different types of values (parameters).To address this problem, we propose a new aggregation method which will suit for different types of local models.To achieve our goal, we transfer knowledge from local models to the global model.To do so, firstly, we propose differentially private GANs, let local parties generate synthetic data related to their training data.Secondly, we use the majority of prediction votes from local models to label those synthetic samples.Finally, use the labelled synthetic data to train the global model.By combining synthetic data and labels from local models, knowledge can be transferred from local models to the global model.We evaluate our scheme on Adult, MNIST and Fashion MNIST datasets under different settings, experimental results show that our scheme can achieve an accurate global model with low privacy loss.Besides, the easily implemented building blocks make our scheme efficient and practical for applications.
Constructing Flow Graphs from Procedural Cybersecurity Texts

Following procedural texts written in natural languages is challenging.We must read the whole text to identify the relevant information or identify the instruction-flow to complete a task, which is prone to failures.If such texts are structured, we can readily visualize instruction-flows, reason or infer a particular step, or even build automated systems to help novice agents achieve a goal.However, this structure recovery task is a challenge because of such texts' diverse nature.This paper proposes to identify relevant information from such texts and generate information flows between sentences.We built a large annotated procedural text dataset (CTFW) in the cybersecurity domain (3154 documents).This dataset contains valuable instructions regarding software vulnerability analysis experiences.We performed extensive experiments on CTFW with our LM-GNN model variants in multiple settings.To show the generalizability of both this task and our method, we also experimented with procedural texts from two other domains (Maintenance Manual and Cooking), which are substantially different from cybersecurity.Our experiments show that Graph Convolution Network with BERT sentence embeddings outperforms BERT in all three domains.
The Reality of Electronic Leadership in Jordanian Schools from the Perspective of Its Teachers

E-leadership has become very essential to be practiced in an environment dominated by accelerating change and high competitiveness. Schools need e-leadership to achieve their e-activities and satisfy their students’ online requirements. Therefore, the current study aimed to assess the reality of e-leadership in Jordanian schools for purpose of enhancing their educational performance. The study population consisted of all Jordanian schools through all Jordanian governorates, and the study sample was composed of (386) teachers from different educational directorates. A self-reported questionnaire composed of (6) dimensions with (36) items, was used for collecting data from the study sample. Descriptive statistics means, and standard deviation were used for data analysis using SPSS tools. It was found that e-leadership is practiced in a medium level by the teachers of Jordanian schools, with e- management practice in the first rank, and E- Team Building practice in the final rank.
AutoText: An End-to-End AutoAI Framework for Text

Building models for natural language processing (NLP) tasks remains a daunting task for many, requiring significant technical expertise, efforts, and resources. In this demonstration, we present AutoText, an end-to-end AutoAI framework for text, to lower the barrier of entry in building NLP models. AutoText combines state-of-the-art AutoAI optimization techniques and learning algorithms for NLP tasks into a single extensible framework. Through its simple, yet powerful UI, non-AI experts (e.g., domain experts) can quickly generate performant NLP models with support to both control (e.g., via specifying constraints) and understand learned models.
Storytelling application based on interactive story graph structure (ISGS) / Hayati Abd Rahman, Azrina Ashaari and Nur Azima Alya Narawi

Storytelling is a process of conveying series of events and information in words, images, and sound. Conventionally, storytelling developers/writers will apply the linear narrative structure approach to deliver the stories. However, that approach has some limitations; users cannot determine the path to end the story. They have no option to choose how to end the story based on their way of storytelling. Therefore, this study is about applying an Interactive Story Graph Structure (ISGS) approach to storytelling. ISGS approach is a structure used in storytelling in which users can revert their decision when going through the storytelling application implemented during the development. After completing the storytelling prototype development, a survey was conducted to test users’ enjoyment level when using the prototype. The survey was divided into four constructs: expectation, ease of navigation, understanding, and satisfaction. There were 36 respondents, and the data were collected on a random basis. Based on the survey’s result, most users (90.28%) enjoyed the storytelling application. The storytelling prototype was developed using Adobe Animate Creative Cloud and has been distributed among the respondents randomly. The analysis was conducted to determine the findings, limitations, and recommendations for future project improvement based on the results obtained. This study’s outcome is the complete production of storytelling application, which is creative and interactive with ISGS.
LEVEL OF ERRORS, CHANGE IN DIAGNOSIS AND THEIR IMPACT ON MANAGEMENT IN CASES REFERRED FOR SECOND OPINION

Objective: To determine the frequency of change in diagnosis and level of errors in cases referred to Armed Forces Institute of Pathology for second opinion and their impact on modifications of treatment and prognosis.&#x0D; Study Design: Cross sectional study.&#x0D; Place and Duration of Study: Department of Histopathology, Armed Forces Institute of Pathology, Rawalpindi, form Mar to Oct 2017&#x0D; Methodology: All the cases referred for review diagnosis were tested by applying panel of immunohistochemical markers and special stains on formalin fixed paraffin embedded tissue sections as decided on morphology. Level of errors were defined as level I error: minor discrepancy with no impact on management, level II: minor discrepancy with impact on management, level III: main category remains same but there was change/confirmation of specific diagnostic entity with an impact on management and level IV: gross changes in diagnosis with significant impact on management. Level IV was further subdivided into IV a: benign misdiagnosed as malignant, IV b: malignant misdiagnosed as benign and IV c: changes in tumor subtype.&#x0D; Results: A total of 100 cases, where review diagnosis was changed were included. Minor discrepancies (level I and level II) were observed in only 7% cases with little or no impact on the management. Most frequent discrepancy observed as Level III in 75% cases. Major discrepancy (Level IV errors) was noted in 18% cases.&#x0D; Conclusion: There were high discrepancy rates between previous diagnosis and review diagnosis. The higher use of extended panels of immunohistochemistry markers were the most likely explanations.
Accelerating Data Discovery with an Ontology-driven Tool for an Enterprise-scale Data Lake Environment

A large overhead in the analytics process is the time required to find relevant data. We present an ontology-driven data discovery application, implemented over IBM’s Cognitive Enterprise Data Platform (CEDP). CEDP contains a large collection of heterogeneous data assets from enterprise-wide data sources. The application accelerates the time required for data consumers to search and find data relevant for their analytics applications.
The Experience In Organizing A Hands-On Course In Physics In E-Learning Environment

The paper considers the issues of organizing Laboratory Practicum when changing to online training in March-April 2020.The authors analyze the possible usage of virtual laboratory works in Physics available on the Internet for distance learning in higher education.It is shown that many hands-on and lab sessions respectively do not allow using virtual labs available on the Internet, at the Physics Department at Pacific National University.There are three main options for doing laboratory works in a remote learning at the department.The authors use electronic courses developed at the department and based on the virtual learning environment Moodle.The researchers do a comparative analysis of the first-year students' performance in Physics in the summer exams of 2019 and 2020.They also analyze the academic performance of 110 students.Remote learning did not affect students' academic performance greatly.They did a survey to compare the degree of students' satisfaction with learning in laboratory classes offline and online.It was done in October 2020 among 66 second-year Engineering students in two majors.It evaluated the training outcomes for the preceding year.The students' answers to the questionnaire are shown in the table as credits.Students highly appreciate the laboratory classes online.At the same time, the marks differ a little from those of the lab works in the classroom.The transition to online training discovered several problems in organizing distance learning.These problems are most referred to the subjects in the syllabus of which laboratory classes are included.
Improving the Performance-Compatibility Tradeoff with Personalized Objective Functions

AI-systems that model and interact with their users can up-date their models over time to reflect new information and changes in the environment. Although these updates may improve the overall performance of the AI-system, they may actually hurt the performance with respect to individual users. Prior work has studied the tradeoff between improving the system’s performance following an update and the compatibility of the updated system with prior user experience. The more the model is forced to be compatible with a prior version, the higher loss in performance it will incur. This paper challenges this assumption by showing that by personalizing the loss function to specific users, it is possible to increase the prediction performance of the AI-system while sacrificing less compatibility for these users. Our approach updates the sample weights to reflect their contribution to the compatibility of the model for a particular user following the update. We construct a portfolio of different models that vary in how they personalize the loss function for a user. We select the best model to use for a target user based on a validation set. We apply this approach to three supervised learning tasks commonly used in the human-computer decision-making literature. We show that using our approach leads to significant improvements in the performance-compatibility tradeoff over the non-personalized approach of Bansal et al., achieving up to 300% improvement for certain users. We present several use cases that illustrate the difference between the personalized and non-personalized approach for two of our domains.
Enhancing Language Generation with Effective Checkpoints of Pre-trained Language Model

This work empirically explores effective exploiting of intermediate output from pretrained language models (PrLMs) for language generation tasks.For this purpose, we propose an improved method to integrate public checkpoints of PrLMs for the most convenience and perform extensive experiments on 6 different kinds of PrLMs, including BERT, ELEC-TRA, GPT2, Multi-lingual BERT, and XLM RoBERTa.Evaluation with automatic metrics shows that our approach significantly improves the generation quality on the generation tasks, up to 1.8 BLEU points for neural machine translation (Korean-to-English, Koreanto-Chinese) and 1.8 ROUGE points improvements for text summarization.
Knowledge Extraction System from English Newspaper

Web has tens of millions of files on any subject matter which can be from any field. It may be very tough for anybody to examine loads of documents to apprehend knowledge approximately any occasion. The aim of my research is to apply extraction technique that can be used for tracking topics. Creating a User Interface (UI) where user can communicate with Application. Extract records from newspapers, articles which can be in e-form as well as from newspapers. Information plays an important role in the human society. Information can be related to many important issues in finance, social science, and marketing. The system is based on the concept that will extract text and altering the structure of web page and the contents which are not relevant like ads and user comments will be excluded.
KONTRIBUSI LAYANAN PERPUSTAKAAN DAN MOTIVASI BELAJAR TERHADAP HASIL BELAJAR SISWA

This research is motivated by the problem of less optimal learning outcomes in DLE subjects in grade X Audio Video Engineering of SMK 1 Koto XI Tarusan, where 51.42% of students get learning outcomes below the Minimum Competency Standards (SKM). The purpose of this study is to reveal the extent of library services and learning motivation towards learning outcomes of DLE subjects in SMK 1 students Koto XI Tarusan 2018/2019 academic year. This research is a descriptive correlational study. The results of the data analysis showed that library services and learning motivation together contributed 25.70% to student learning outcomes in SMK 1 Koto XI Tarusan, library services contributed 69.55% to student learning outcomes in SMK 1 Koto XI Tarusan, Motivation learning contributed 16.32% to student learning outcomes in SMK 1 Koto XI Tarusan. So it can be concluded that library services and motivation to learn contribute to learning outcomes. The more optimal library services and the higher motivation to learn, the more optimal learning outcomes will be. Keywords: Library Services, Learning Motivation, Learning Outcome,
TO THE STUDY OF SOCIAL-PSYCHOLOGICAL READYNESS OF SENIOR GRADE STUDENTS REGARDING PROFESSIONAL CHOICE

Today it is extremely necessary to modernize the system of vocational guidance in Ukraine in accordance with the requirements of a market economy of content, forms and methods of career guidance, as well as public demands and achievements of prominent scientists on professional development and personal development. Thus, there is a need to critically rethink the past, improve its achievements and enrich it with the best examples of world science and practice. This will allow us to learn the signs of imbalance between supply and demand in the labor market, to determine the prospects for the development of theory and methods of vocational guidance for children, youth and adults in Ukraine. In modern conditions of socio-cultural development, the relevant qualities of a young person are not only the general educational level, but also the level of culture, socio-psychological competence, ability to think critically, the presence of their own point of view on social processes and problems. School graduates face the problem of choosing a way to prepare for a future profession. Often vocational training in an institution is chosen at random. Half of school graduates are immediately employed without special training and therefore professional career prospects. Modern technologies of career guidance work are designed to provide conditions for a person to realize his attitude to himself as a subject of professional work and behavior, which aims to independently search for professions taking into account their own interests and capabilities, and then the labor market. The purpose of the article is a theoretical analysis of the scientific problem of socio-psychological readiness of high school students to enter higher education institutions, the disclosure of the problem of professional self-determination of the individual in market processes. Research methods used: analysis of psychological and pedagogical literature; comparative-historical method of foreign and domestic experience in the study of socio-psychological readiness as a socio-psychological phenomenon.
Use of Hands up Media to Improve Students' Speaking Ability in English

Among the success of education is due to the quality of learning. The quality of learning is good because of the use of teaching aids. Likewise, the success of listening material is also supported because of the accuracy of the use of teaching aids. Here there is the use of practical teaching aids that can improve the quality of learning English, especially speaking material. Sources of data include 30 students consisting of 15 students. Data were collected through observation and documentation. To analyze the research data used descriptive quantitative methods with percentages. The percentage results are then consulted with predetermined criteria. The results show the effectiveness of hand puppet props in learning and improving students' abilities. Students become more active and motivated by the presence of hand puppet props. Props can increase students' learning motivation, thus supporting a learning atmosphere for students. The results of the evaluation of learning activities are generally good, as seen from the aspects of material suitability, understanding, analysis and synthesis, and learning intensity.