Reviewerly/exHarmony huggingface dataset:
The Mechanism of Using e-learning at the University of Misan from the Point of View of the Teaching Staff Members

E- Learning is considered as an interactive system for education by using communication and information technology relied on an electronica digital environment and by the latest methods of learning, tests and guidance and counseling by using computers and its networks and mass media, and smart phones. After the outbreak of (covid -19 pandemic) and the application of the quarantine in Iraq, the university of Miasn directly supplied study materials to the students as a solution that help to complete the academic year so the researcher decided to choose this experience as a field study of the current study. The recent study aims at: 1. Identifying the use of E-learning from the point of view of the teaching staff of Misan University. 2. Identifying the pros and cons of using E-learning from the viewpoint of the teaching staff of Misan University
Investigación en el aula: un trabajo colegiado

espanolEl trabajo colegiado implica la oportunidad de compartir con los colegas las dificultades y los logros alcanzados al interior de cada aula, para optimizar los esfuerzos y lograr el aprendizaje de los estudiantes. Al buscar la generacion de conocimiento academico, se procura una investigacion que incide directamente en el aula, el docente frente a grupo es el actor principal en estas investigaciones, y al incluir la investigacion en el aula como parte del trabajo colegiado se generan comunidades tanto de aprendizaje como de investigacion. El objetivo del presente articulo es documentar el tipo de trabajo colegiado que se lleva a cabo durante la investigacion en el aula. Los docentes que trabajan de esta manera son capaces de producir conocimiento academico; en la investigacion se busco una respuesta a la pregunta ?como debe ser la retroalimentacion para colaborar en el aprendizaje de los estudiantes? EnglishTeacher team work implies the opportunity for sharing with colleagues the difficulties overcame and achievements reached in the class in order to optimize the efforts and achieve students learning. Attempting to produce academic knowledge, the working team does a research that begins directly in the classroom; class teacher is the first protagonist in such research; with the integration of this kind of class research as part of the activities of the working team we are building a learning as well as a research community. The main objective of this paper is to document this kind of team work activities developed in the class research. Teachers working in this way may be able to produce academic knowledge; we were looking for an answer to the question, how should the feedback be in order to foster student learning?
Back Camera [1.36.X]

Rear camera for all trucks. Press the 5 key to switch to the rear camera. Priority in the mod manager is not
Essential Ethics for Immersive Learning Practitioners

This presentation will introduce essential ethical issues for XR practitioners working in educational, commercial or entertainment application areas. While many of the underlying ethical issues are fundamentally the same as those experienced with other digital technologies (such as games, virtual worlds, social media), the immersive nature of extended reality applications can bring issues into sharper relief with potentially more significant consequences. With a rich history of problematic use of information systems and growing awareness of how technology can help embed inequalities and inequities, ignorance is no excuse.In this presentation, and the following discussion, we'll explore a range of case studies that highlight ethical challenges that XR developers are likely to encounter or where failure to consider issues has led to real problems and negative user experiences in XR. We will also explore published ethics guidelines and professional codes of conduct that may be helpful for XR practitioners.
Enhancing Context-Based Meta-Reinforcement Learning Algorithms via An Efficient Task Encoder (Student Abstract)

Meta-Reinforcement Learning (meta-RL) algorithms enable agents to adapt to new tasks from small amounts of exploration, based on the experience of similar tasks. Recent studies have pointed out that a good representation of a task is key to the success of off-policy context-based meta-RL. Inspired by contrastive methods in unsupervised representation learning, we propose a new method to learn the task representation based on the mutual information between transition tuples in a trajectory and the task embedding. We also propose a new estimation for task similarity based on Q-function, which can be used to form a constraint on the distribution of the encoded task variables, making the task encoder encode the task variables more effective on new tasks. Experiments on meta-RL tasks show that the newly proposed method outperforms existing meta-RL algorithms.
Deep Feature Generation for Author Identification

Identifying the authors of a given set of text is a well addressed and complicated task. It requires thorough knowledge of different authors’ writing styles and discriminating them. As the main contribution of this paper, we propose to perform this task using machine learning and deep learning methods, state-of-the-art algorithms, and methods used in numerous complex Natural Language Processing (NLP) problems. We used a text corpus of daily newspaper columns written by thirty authors to perform our experiments. The experimental results proved that document embeddings trained via neural network architecture achieve cutting edge accuracy in learning writing styles and identifying authors of given writings even though the dataset has a considerably unbalanced distribution. We represent our experimental results and outsource our codes for interested readers and natural language processing (NLP) enthusiasts as a GitHub repository. They can reproduce and confirm the results and modify them according to their own needs.
Natural Language Processing for Patient Data in Clinical Decision Support Systems

In Sweden, prostate cancer is the most common type of cancer among men. The care need within prostate cancer will get higher as the population increases and gets older. With this in mind, there is a need to streamline the care pathway. One way to do this is with a clinical decision support system. Here natural language processing (NLP) plays an important role to handle the big amount of free text data. In this project, we used NLP, more specific text classification and information extraction. The task was to extract key information related to prostate cancer from free text in electronic health records. The key information that we chose to extract were Gleason, PSA and tumour type. Binary classifiers were used to sort out irrelevant texts, to reduce the complexity for the information extraction. We tried different classifiers and methods to extract information. The information extraction method which turned out to be the best was named entity recognition (NER). Another important part of the project was to map the care pathway and data-flow within prostate cancer. To build our algorithms, we mainly used the open source library for text processing called Spacy. The classifiers with the overall best performance were random forest (F-score in average 0.978) and Swedish Spacy CNN (F-score in average 0.965). For the named entity recognition, we used Swedish Spacy CNN and Swedish BERT. The Swedish Spacy CNN in average got F-score of 0.915 while the Swedish BERT got 0.922. In the final and best pipeline, we combined one binary classifier (prostate cancer related or not) with the Spacy CNN NER and got F-score of 0.911.
Hornblaster Train Horn Xl For P8 Horns

Don’t Blow Your Temper, Blow Your Horns! HornBlaster Train Horn XL for P8 Horns, you will need Powerkasi addons v1.2 to use this mod. Place this mod ...
ANALISIS BIPLOT UNTUK RETURN ON ASSET (ROA) DAN RETURN ON EQUITY (ROE) PADA PERUSAHAAN ASURANSI JIWA NASIONAL

Biplot analysis is a type of multivariate analysis used to solve problems or process data that involves many variables. The number of variables in a data often makes it difficult to represent the results. Therefore, Biplot is a media solution for describing the data in the summary table in a two dimensional graph. This analysis can be applied to find out information about the relative position, similarity of characteristics between objects and the diversity of variables or variables in the elements of return on assets and return on equity in national life insurance companies related to aspects of a health assessment and company grouping. The results of the biplot analysis show two categories, namely grouping based on biplot points and year variability. There are differences in the results of national life insurance groupings, namely the AJB Bumiputera 1912 company, Central Asia Raya Life Insurance, Equity Life Indonesia, Heksa Solution Insurance, Jiwasraya Insurance, Indosurya Sukses Life Insurance. Meanwhile, national life insurance companies that have the same characteristics for return on assets and return on equity are divided into 3 (three) groups. In the management aspect, namely related to life insurance companies that are stable and healthy in investing, ROA and ROE are shown by group III. The greatest and most dominant diversity of years for return on assets lies in 2018, while for return on equity, the greatest diversity is in 2019. There is a difference in the results of the variation in ROA and ROE due to the variable used differently. ROA shows aspects of assets consisting of liabilities and equity. If the acquisition of large assets, it can be used to pay corporate liabilities. ROE only shows from the side of equity without paying attention to liabilities.
RANCANG BANGUN MADIA PEMBELAJARAN MULTIMEDIA INTERAKTIF PADA MATA PELAJARAN DASAR DESAIN GRAFIS

Graphic Design is one of the required subjects of expertise package for Vocational students in Multimedia majors. These Graphic Design subjects are more directed at competency-based practicum which aims to equip students' skills in the field of graphic design so that students have strong skills with realistic theoretical foundations for students. Therefore there are still many students who do not understand the learning given by the teacher because the teacher has not used different techniques in delivering learning material, therefore it is necessary to design interactive learning media so that the teacher is easy to apply learning material and help students master the subject matter. In designing basic Graphic Design learning materials using explicit intruction models and through Interactive Multimedia learning procedures, starting from the needs analysis in designing, gathering data, identifying material to determining learning flow chart design, material collection or graphic needs. The interactive multimedi learning media is designed using the adobe director 11 application, and other applications such as Adobe Photoshop, Coreldraw, Camtasia as supporting applications so that it becomes an interactive multimedia learning media application that provides convenience for students in learning.Keywords: Learning Media, Interactive Multimedia, Graphic Design.
Use of infographics for the development of cadets’ speaking skills at foreign language classes

The search for effective tools used in teaching English in a military college within the constraints posed by limited time resources is a top problem of foreign language learning theory and practice. The implementation of the principle based on visual aids involves the visualization of linguistic and socio cultural material at foreign language classes and fulfills the requirements of new federal educational standard to the educational process in a higher educational institution, creates the conditions of better assimilation of information studied at the lesson, and encourages cadets to speaking activities. The author gives a very detailed analysis of the infographic method, as a mean of developing students’ communication and speaking skills, relating to the field of foreign language teaching. In the present article it is considered as a graphic way to present the information that combines text material, as well as graphic elements, which provide a visual support for speaking monologue on the topic. The didactic ability of the use of infographics at practical English classes was analyzed by the author. The detailed description of the pedagogical objectives, reached by means of this method, its advantages, possibility of its use for solving educational problems at different lesson stages was given. The methodological recommendations for the purposes of organizing infografic-based activities at English classes and the plan of speaking monologue (support scheme) on infografics were proposed for use. Also, the examples of tasks based on the infographic method, which can be used at foreign language classes in a military college, were given.
CNN-based method with self-supervision for visual place recognition

An open problem in the artificial intelligence community is built an algorithm to able geo-localize a given photo, overcoming the multiple problems related to the domain shift between the images used during the training and the ones passed at test time. During this thesis, our contribution didn’t just focus on research but we have also implemented a software that is easy to use for any kind of user, as well as creating a dataset that can be used for further research. In order to exploit the VPR problem with a deep learning method, we have used the current state-of-the-art CNN called NetVLAD [1], that we have properly modified to speed up the process and for studying the results on our dataset. In particular, we have tested the final network with a third-domain dataset and tried also a self-supervision approach, to make the network more confident with the different domains belong to training and testing phases. Moreover, we have also partially investigated the effect of some artificial occlusions on the image that needs to be geo-localize, seeing if they can be useful to focus the network attention on the relevant object inside a photo, instead of the dynamic ones. Finally, two kind of software are developed, the first one is composed by a set of steps, to download and create all the necessary stuff related to the dataset that a user want to create, while the second one is a graphical user interface, used to upload a photo and visualize the network results.
Designing a smart contract process model based on blockchain technology Using Meta-Synthesis Research Method

Due to the growing future of blockchain applications such as smart contracts and the widespread use of smart contracts in the Internet of Things (IoT) and the lack of Persian resources in this field, it is necessary to conduct comprehensive and integrated researches for a systematic study of past studies and provide interpretive perspectives and create new knowledge. In this research, using mixed research method (first, using the Meta-Synthesis Research Method, by combining qualitative findings of previous studies and combining different perspectives, a model in the process of smart contracts on the blockchain platform is presented and then for evaluation and analysis of the modeled, structural equations quantitative method and confirmatory factor analysis with Smart PLS3 software have been used. The lack of a standard framework for analyzing and comparing smart contract-based systems identifies the need to design a smart contract model that allows smart contract developers to identify bottlenecks and improve system-based smart contracts.
COVID-19 NEWS AND AUDIENCE AGGRESSIVENESS: ANALYSIS OF NEWS CONTENT AND AUDIENCE REACTION DURING THE STATE OF EMERGENCY IN LATVIA (2020–2021)

This research focuses on the interrelation between news content on COVID-19 of three largest online news sites in Latvia (delfi.lv, apollo.lv, tvnet.lv) and the audience reaction to the news in the Latvian and Russian channels during the state of emergency. By using a tool for audience behaviour analysis, the Index of the Internet Aggressiveness (IIA), for analysis of audience comments, the study aims to uncover how and whether news about COVID-19 affect the level of audience aggressiveness. The study employs two data collection methods: news content analysis and IIA data analysis, in which ten index peaks are selected in each of the two emergency periods (spring 2020, fall and winter 2020/21). The study data consists of content analysis of 400 news items and analysis of ~80,000 comments, identifying the level of aggressiveness, the number and structure of comment keywords. The results show that the level of public aggressiveness is only partially formed by the attitude towards COVID-19 news: less than half of the most aggressively commented news is devoted to information about COVID-19. An increase in the level of aggressiveness of the audience of online news sites can be observed at the end of 2020 and at the beginning of 2021 when it is higher than over the course of 2020.IIA is an online comment analysis platform, which analyses user-generated comments on news on online news sites according to pre-selected keywords, allowing to grasp the dynamics of commenters’ verbal aggressiveness. In addition, IIA exploits a machine learned classifier to recognize not only potentially aggressive keywords but also to analyse the entire comments. In January 2021, the IIA data set consists of ~24.89 million comments (~611.97 million words) added to ~1.34 million news articles.
PEMBELAJARAN BERBICARA BERBANTUAN KOMIK STRIP UNTUK PEMBELAJAR BIPA KOREA SELATAN

Speaking skill is a very complex skill because it involves other skills. Especially in BIPA learning, relevant strategies are needed as an alternative to learn BIPA. Therefore, this study is intended to describe the results of learning process by using comic strip toward speaking practice. Based on the tracing of previous studies, it was not found any research related to the use of comic strips in learning to speak BIPA. The method used in this research is qualitative. The participants in this study were South Korean BIPA learners in intermediate levels of ability. The results of the data analysis show that learning to speak using comic strip can be an alternative in teaching BIPA. This can be seen in all activities which run effectively. In addition, learners also give very positive responses during learning
Phishing Website Detection using Machine Learning

Phishing is not a legal activity, in this people are misguided into the wrong websites using various types of fraudulent methods. The main objective of this phishing websites is to seize all personal information or financial details for own personal benefits or misuse. As the technology facilitates, the phishing approaches used needs to get progressed and therefore there is urgent need for better security and better mechanisms to prevent as well as detect this phishing approaches. The primary focus of this paper to put forward a model as a solution to detect phishing websites by using the URL detection using Random Forest Algorithm. There are basically three major phases such.
Fault Inspection of Brake Shoe Wear for TEDS Based on Machine Vision

With rapid development of high-speed railway, the automated inspection of related faults is prerequisite for ensuring the safety of the EMU movement. As similar as TFDS in moving freight trains, TEDS is also applying in fault detection of the running EMU. Brake shoe is one of the key components in brake system, and the pre-warning on wear limitation about it is very important in the fault detection on EMU. In this paper, we propose a real-time, automated inspection method to detect the wear limitation of the brake shoe. Firstly, multi-resolution pyramid template matching technology is used for fast localization of the brake shoe. Then, LSD and Hough transform are employed to detect the wear limitation of the brake shoe. The experiments demonstrate that the way is high efficiency and well real-time, and it can meet the need of practical application.
A Simple Framework for Cognitive Planning

We present a novel approach to cognitive planning, i.e., an agent's planning aimed at changing the cognitive attitudes of another agent including her beliefs and intentions. We encode the cognitive planning problem in an epistemic logic with a semantics exploiting belief bases. We study a NP-fragment of the logic whose satisfiability problem is reduced to SAT. We provide complexity results for the cognitive planning problem. Moreover, we illustrate its potential for applications in human-machine interaction in which an artificial agent is expected to interact with a human agent through dialogue and to persuade the human to behave in a certain way.
Visualization tools: for the OpenQL compiler

The rapid progress quantum devices have made in recent years has led to the need for systems that bridge the gap between quantum algorithms and quantum hardware. To this purpose different full-stack quantum programming platforms have been developed, providing high level languages for expressing quantum algorithms and providing compilers for making those quantum algorithms executable on a given quantum device. OpenQL is one such a platform, with support for compiling a variety of quantum program inputs into a quantum circuit, ready to be executed on the targeted quantum hardware. OpenQL is an evolving tool in which new features are constantly added to improve its performance and extend its functionality. In order to enhance OpenQL and provide some extra support to the researchers using OpenQL for their experiments, a visualization tool with three main functionalities has been developed in this thesis project. First, a circuit visualizer, with support for both visualizing the circuit output of the OpenQL compiler as an abstract gate representation and a pulse representation, which has been made specifically for quantum hardware running on superconducting qubits. Secondly, a mapping graph visualizer, which allows displaying the logical to physical qubit mapping per program cycle. And lastly a qubit interaction graph generator, which shows the required interactions between qubits of a given quantum algorithm.
THE INFLUENCE OF STUDENTS’ ATTITUDE AND PERCEPTION ON SCIENTIFIC APPROACH TOWARD THEIR ENGLISH ACHIEVEMENT AT SMA MUHAMMADIYAH 11 PADANGSIDIMPUAN

The purpose of this study was found out the influence of Students’ Attitude and Perception on Implementing the Scientific Approach Toward their English Achievement at SMA Muhammadiyah 11 Padangsidimpuan. This study was a correlational research design of expo facto using two independent variables and one dependent variable, Students’ attitude (X1) and Perception (X2) were independent variables, and English achievement (Y) as dependent variable. Three research questions were stated in this research. There were 41 respondents of the eleventh grade students of SMA Muhammadiyah 11 Padangsidimpuan. Total sampling was used in this research because the number of students was not so many. Data of students’ attitude and perception were collected using questionnaires of Likert’s scale, while the students’ achievement was taken from a documented data. The data were analysed by using Product-Moment formula and the analysis of variance for multiple regressions data. Three hypotheses were stated in this research. The result of the first hypothesis is showed that students’ attitude toward English achievement had more significant influence compared to the second hypothesis of the influence of the students’ perception through scientific approach on students’ English achievement. At last, the finding can be concluded that there were significant influences of students’ attitude and perception toward the English achievement of the students at SMA Muhammadiyah 11 Padangsidimpuan. Keyword: Students’ attitude, perception, scientific approach, English achievement.