Reviewerly/exHarmony huggingface dataset:
DEVELOPMENT OF HIGHER ORDER THINKING SKILLS (HOTS) AS FRENCH LANGUAGE TEACHING ASSESSMENT INSTRUMENT AT SMA NEGERI 11 MEDAN

This research is aimed at determining the process, suitability and effectiveness of HOTS as the assessment instrument and involves students of class XI IPS-4 at SMA Negeri 11 Medan, Indonesia. The method is a quantitative and descriptive in which all collected data is analyzed using descriptive statistical techniques expressed in the distribution of scores and scale categories. This study is validated by the material and evaluation validators. The instruments include the assessment guide, the assessment instrument response, quiz sheets for validators, quiz sheets for students, and learning outcome tests. The process of developing HOTS-based assessment instruments in Class XI IPS-4 SMA Negeri 11 Medan consists of 4 stages, namely: test preparation, media selection, format selection and test results design. The results show that the validation by the materials validator reached on average of 93.02% (very good) and by evaluation validators was noted to 91%, (very good). In the pre-test and post-test activities, on the pre-test there were 2 pupils (6.06%) included in the thinking category of a higher level (very good), 5 pupils (15.15%) (good), 15 students (45.45%) (fairly well), 8 students (24.24%) (not well) and 3 students (9.09%) with an average score of 48.12 (poor). In the post-test, there were 7 students (21.21%) in the very good category, 21 students (53.63%) were in the right category and 5 students (15.15%) with an average score of 74.91 were in the correct category. (21.21%) so that the results of post-test activities in the form of description questions were much better than those of post-test activities with the same form of questions.
Transformando el Programa Intensivo sobre el Futuro de la Banca y Las Finanzas en un encuentro virtual

espanolEl estallido de la pandemia originado por el virus SARSCOVID 19 ha obligado a un replanteamiento de nuestra vida en todos los ambitos. Inmersos en este nuevo contexto, y con el objeto de continuar ofreciendo a nuestros estudiantes una formacion integral que incluya no solo conocimientos, sino tambien competencias, que les permitieran incorporarse a un mercado laboral que tambien se ha transformado radicalmente, se decidio convertir el Programa Intensivo sobre el Futuro de la Banca y las Finanzas en un evento virtual. Durante seis meses se trabajo en un nuevo planteamiento, que ha permitido a los estudiantes participantes continuar trabajando de manera colaborativa en un entorno multicultural. EnglishThe outbreak of the pandemic caused by the SARS-COVID 19 virus has forced us to rethink our lives. Immersed in this new context, and with the aim of continuing to offer our students a comprehensive training that includes not only knowledge but also skills that will enable them to join a labour market that will also have to adapt to this new situation in the short term. With this objective in mind, the decision was taken to transform the Intensive Programme on the Future of Banking and Finance into an online event, in which the participating students would continue to work collaboratively in a multicultural environment.
Impacto de la plataforma Microsoft Teams en el proceso docente de la Unidad Educativa “José Alejandro Bermúdez Farías”

The present work reveals the impact that the use of the Microsoft Teams technological platform in the teaching process has had for teachers and students of the Jose Alejandro Bermudez Farias Educational Unit from the epidemiological situation caused by COVID-19. Distance education is assumed as a relevant reference for research, as it provides theoretical, methodological and technological foundations of capital importance. Likewise, the procedural, methodological, contextual and technological dimensions that characterize the teaching process are presented. As part of the research process, various information gathering methods and techniques were used.
Detect and Classify – Joint Span Detection and Classification for Health Outcomes

A health outcome is a measurement or an observation used to capture and assess the effect of a treatment. Automatic detection of health outcomes from text would undoubtedly speed up access to evidence necessary in healthcare decision making. Prior work on outcome detection has modelled this task as either (a) a sequence labelling task, where the goal is to detect which text spans describe health outcomes, or (b) a classification task, where the goal is to classify a text into a predefined set of categories depending on an outcome that is mentioned somewhere in that text. However, this decoupling of span detection and classification is problematic from a modelling perspective and ignores global structural correspondences between sentence-level and word-level information present in a given text. To address this, we propose a method that uses both word-level and sentence-level information to simultaneously perform outcome span detection and outcome type classification. In addition to injecting contextual information to hidden vectors, we use label attention to appropriately weight both word and sentence level information. Experimental results on several benchmark datasets for health outcome detection show that our proposed method consistently outperforms decoupled methods, reporting competitive results.
The effect of COVID-19 on law libraries: Are these changes temporary or a sign of the future?

This article was originally published in Volume 60(1) (2020) of the 'Washburn Law Journal' pages 107-129 – available at https://contentdm.washburnlaw.edu/digital/collection/wlj/ id/7279/rec/61. The...
Digitalization of higher education, the crisis of educational culture and Russian economic development

The problems of digitalization of education and transformation of the Russian culture has been overlooked in the research space. The aim of this research therefore is to report the crisis nature of Russian educational culture, considered in terms of digital innovations of the higher education system. The study was qualitative, and it utilized the transdisciplinary paradigm as a methodological framework. Data was drawn from previous research in different disciplines regarding the topic of interest and the results were analyzed using content analysis. This helped the research to form a holistic view of the phenomena under consideration. The results prove the need to develop a holistic social and philosophical concept of cultural transformation of Russian education to solve the problems and contradictions of transition to digital education and increase the economic growth. Keywords: education, higher education, digitalization of education, digitalization, informatization, onlineization, imitation, culture, culture of education, economic development
Path Planning of Unmanned Helicopter Based on an Improved Artificial Bee Colony Algorithm

This paper mainly investigates an improved artificial bee colony (ABC) algorithm on path planning of the unmanned helicopter. First, the dynamic evaluation selection strategy is used to optimize the follow way of on-looker bees for improving the optimization efficiency of the ABC algorithm. Second, the related-track point method is employed to ensure that the original track points satisfy the constraints of path planning, thereby improving the quality of the flight path. Simulation results confirm that the developed path planning method of unmanned helicopter based on improved ABC algorithm has satisfactory performance.
Moser Flow: Divergence-based Generative Modeling on Manifolds

We are interested in learning generative models for complex geometries described via manifolds, such as spheres, tori, and other implicit surfaces. Current extensions of existing (Euclidean) generative models are restricted to specific geometries and typically suffer from high computational costs. We introduce Moser Flow (MF), a new class of generative models within the family of continuous normalizing flows (CNF). MF also produces a CNF via a solution to the change-of-variable formula, however differently from other CNF methods, its model (learned) density is parameterized as the source (prior) density minus the divergence of a neural network (NN). The divergence is a local, linear differential operator, easy to approximate and calculate on manifolds. Therefore, unlike other CNFs, MF does not require invoking or backpropagating through an ODE solver during training. Furthermore, representing the model density explicitly as the divergence of a NN rather than as a solution of an ODE facilitates learning high fidelity densities. Theoretically, we prove that MF constitutes a universal density approximator under suitable assumptions. Empirically, we demonstrate for the first time the use of flow models for sampling from general curved surfaces and achieve significant improvements in density estimation, sample quality, and training complexity over existing CNFs on challenging synthetic geometries and real-world benchmarks from the earth and climate sciences.
An Art Class for Music

This chapter describes in detail a constructivist philosophy for music curricula. Alternatives to traditional performance ensembles, including songwriting, sound design, remixing, sampling, and other computer-based music creation techniques, are discussed. The constructivist approach adopts learning strategies used by popular musicians, including aural learning by listening to and copying recordings, and personal learning with minimal adult guidance and intervention. Furthermore, project prompts are designed to guide students from tightly scaffolded and formulaic production exercises to more open-ended creative projects. The affordances of digital audio workstations support trial-and-error experimentation by linking visualization to immediate auditory feedback for each action. The chapter also covers the role of sound design in popular music production, the remix as a scaffold for creating original songs, and the intellectual property considerations inherent in sampling. The goal is for students to have created a portfolio of music that expresses their tastes and identities, and that they are proud of.
ISP NETWORK FUNCTION BASED PERFORMANCE ANALYSIS ON VIRTUALIZATION USING CLOUD COMPUTING

With advancement of technology, cloud computing gains vital importance in research. People and processes are moving over the cloud that cause to exponential increase in network, storage and computational resources. This exponential growth leads towards large and scalable clouds that costs high in terms of design, deployment and maintenance. The amount of data is increasing day by day due to large amount of cloud users. Resources or services are configured over cloud using virtualization technologies as per user demand. Various virtualization techniques are used for resource allocation. Network function virtualization (NFV) is function based well-known technique to virtualize the functionalities of network while the resources of cloud network will be determined using capital expenditure (CAPEX). This research paper calculates the impact of network function virtualization on CAPEX for cloud-oriented networks and performs comparative analysis between NFV and traditional technologies of virtualization. A prototype to implement NFV over cloud network is designed for experimentation and multiple test cases are executed for performance evaluation. Experimental results show that the overall cost for management and CAPEX is reduced in NFV based implementation of cloud networks. CPU also performing well in case of users or load increment.
LibGuides: A LibGuide for ECE's: Cite Sources

Are you in the Early Childhood Education program at Algonquin College? Check out this guide for information to help you with your program! Contains resources to aid with proper citation.
Qubit Gate Quality Loss Through Circuit Parasitics and Noise

This work aims to find signal sequences that implement high-quality logic gates for single GaAs qubits in a quantum computer. To achieve that an optimization of the gate quality with a scalable electronic architecture in mind is done. In addition, a behavioral model of the qubit and the control electronics in the Q-Interface is implemented. The electronic model includes typical integrated circuit impairments such as process variations and parasitic capacitors. While the initial quality of the optimized gates is high, simulations with the implemented model show partly large quality reductions for some impairments. A major quality loss is for example caused by parasitic capacitors, but some non-ideal effects can be mitigated through pre-distortion, among others.
Federal Constitutional Challenges to the OSHA COVID-19 Vaccination Mandate

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Risk Management by Implementing Hazard Identification, Risk Assessment and Determinant Control (HIRADC) Method in the Research Center of the University in Surabaya, Indonesia

The Research Center of the Faculty of Dentistry, Universitas Airlangga is one of workplaces that have various risks to cause occupational accidents.The use of various chemicals, specimens, and special instruments at the Research Center has potential to cause various risks that can threaten workers, assets, and environment.To prevent and control every hazard with potential negative risks, a risk management using HIRADC method must be implemented.This study aims to implement Hazard Identification, Risk Assessment and Determinant Control (HIRADC) method in the Research Center of the Faculty of Dentistry, Universitas Airlangga.This study is descriptive research with a cross-sectional design.Data collection was done through direct observation in the workplace and interview with a laboratory worker at the Research Center.The Research Center of the Faculty of Dentistry, Universitas Airlangga has a moderate risk.The research results showed that of the 5 work activities, there were 20 potential hazards with 20 risks identified.Based on the risk assessment, there are 1 extreme risk, 1 high risk, 11 moderate risks, and 7 low risks.The extreme risks identified are explosion, fire, and death caused by LPG.The high risks identified are explosion, poisoning, and death caused by CO 2 gas.Based on the determinant control, there are 15 controls implemented including substitution control, engineering control, administration control, and wearing personal protective equipment.However, there are still 5 controls that have not been implemented.Further recommendations are needed for 5 controls that have not been implemented in every activity conducted in the Research Center of the Faculty of Dentistry, Universitas Airlangga.
Adaptive Workflow Scheduling to Increase Fault Tolerance in Cloud Computing

Cloud computing in the field of high-performance distributed computing has emerged as a new development in which the demand for access to resources via the Internet is presented in distributed servers that dynamically scale Are acceptable. One of the important research issues that must be considered to achieve efficient performance is fault tolerance. Fault tolerance is a way to find faults and failures in a system. Predicting and reducing errors play an important role in increasing the performance and popularity of cloud computing. In this study, an adaptive workflow scheduling approach is presented to increase fault tolerance in cloud computing. The present approach calculates the probability of failure for each resource according to the execution time of tasks on the resources. In the present method, a deadline is set for each of the tasks. If the task is not completed within the specified time, the probability of failure in the source increases and subsequent tasks are not sent to the desired source. The simulation results of the proposed method show that the proposed idea can work well on workflows and improve service quality factors.
ВЫБОР ДИСТРИБУТИВА ПРОГРАММНОГО ОБЕСПЕЧЕНИЯ ДЛЯ ИНДУСТРИАЛЬНЫХ И БОРТОВЫХ СИСТЕМ, ИСПОЛЬЗУЮЩЕГО ТЕХНОЛОГИЮ ЗАЩИЩЕННЫХ ВЫЧИСЛЕНИЙ АРХИТЕКТУРЫ ≪ЭЛЬБРУС≫

This research is aimed to feasibility of full software stack on security computing technology of «Elbrus» architecture. We consider on software stack components and make a component chosen for future ports to protected computing mode of «Elbrus» architecture. We also describe uClibc library’s parts and library porting stages on protected computing mode.
THE EFFECTIVENESS OF 3-2-1 STRATEGY ON STUDENTS' READING ACHIEVEMENT OF RECOUNT TEXT IN THE EIGHTH GRADE AT MTs DARUL HUDA WONODADI

As one of the English skills, reading is considered as a tool to access the information. By reading, the students will get much information and knowledge that is very useful for them in learning process. Reading achievement is becoming very important, but in fact many students are still having difficulty in comprehending the reading text. Thus, the teacher should provide the students with suitable teaching strategy to help students increase their reading comprehension. One strategy that can be used by teacher and students in reading is 3-2-1 Strategy. It is a reading strategy that requires students’ participation on summarizing ideas from the text, encourages them to think independently, and invite them to engage with the text. Based on explanation above, the writer intended to apply 3-2-1 Strategy to increase students’ reading comprehension of recount text in the eighth grade at MTs Darul Huda Wonodadi.The formulation are of research problems in this study: (1)How is the students’ achievement of recount text taught by using 3-2-1 strategy? (2)How is the students’ achievement of recount text taught without using 3-2-1 strategy? (3)Is there any significant different scores of students’ reading achievement of recount text taught by using 3-2-1 strategy and without using 3-2-1 strategy? The objectives of this research are: (1)To investigate the students’ achievement of recount text taught by using 3-2-1 strategy. (2)To investigate the students’ achievement of recount text taught without using 3-2-1 strategy. (3)To find out whether there is significant different scores of students’ reading achievement of recount text taught by using 3-2-1 strategy and without using 3-2-1 strategy.Method of this research: The researcher used Quasi-Experimental research using quantitative approach with experimental class and control class. The population of this study was all the eighth grade students at MTs Darul Huda Wonodadi. The sample of experimental group was VIII B and the sample of control group was VIII A. The results of this study showed that there is significant different scores of students’ reading achievement of recount text taught by using 3-2-1 strategy and without using 3-2-1 strategy in the eighth grade at MTs Darul Huda Wonodadi. It can be seen from the mean of students’ score of experimental group that taught by using 3-2-1 Strategy on students’ reading achievement was 78.67. While the mean of students’ score of control class that without using 3-2-1 Strategy was 61.36. The P-value (Sig. 2-tailed) is 0.000 and the significance level is 0.05. Since 0.000 is smaller than significance level (α) 5%. The null hypothesis is rejected. In other word, the hypothesis saying that the mean of experimental group is smaller than or equal to the mean of control one is rejected. The conclusion is that 3-2-1 Strategy is effective for increasing students’ reading achievement of recount text.
Building AR-VR Applications in Unity Software

Unity Software is a powerful 3D and 2D Game Engine, apart from building games it can be used for generating a variety of other applications such as developing of AR (Augmented Reality), VR (Virtual Reality), XR (Extended Reality) and many more. This paper focuses on the concept of Game Engine and discusses the method to build Games in Augmented Reality and  Virtual Reality Applications with some examples..
Does Vision-and-Language Pretraining Improve Lexical Grounding?

Linguistic representations derived from text alone have been criticized for their lack of grounding, i.e., connecting words to their meanings in the physical world. Vision-and- Language (VL) models, trained jointly on text and image or video data, have been offered as a response to such criticisms. However, while VL pretraining has shown success on multimodal tasks such as visual question answering, it is not yet known how the internal linguistic representations themselves compare to their text-only counterparts. This paper compares the semantic representations learned via VL vs. text-only pretraining for two recent VL models using a suite of analyses (clustering, probing, and performance on a commonsense question answering task) in a language-only setting. We find that the multimodal models fail to significantly outperform the text-only variants, suggesting that future work is required if multimodal pretraining is to be pursued as a means of improving NLP in general.
LibGuides: A LibGuide for Film Studies: Home

Welcome to the film studies LibGuide! If you are a film studies student or simply have an interest for film, this guide will help you out.
The Ethical Switch: An Automated Policy and Regulation Framework for Data Dissemination in Cloud Environments

A significant amount of research has gone into putting in place the ideal ethical policies and regulation frameworks for Information Systems. However, new fields of Information Technology have seen the birth of cloud computing, artificial intelligence, big data and internet of things extending the horizons of ethical boundaries to very complex territories. Existing Ethical controls have been limited to focusing mostly on the aspect of human behaviour with an aim of preventing the occurrence of many ethical accidents. This study proposes a technical approach to enforcing ethical control known as the Ethical Switch (ES here forth) in the dissemination of data in the Cloud environment. This approach works by modelling data dissemination in a digital ecosystem consisting of three parties: a data recipient, a data donor, and a neutral regulator. A generic policy iteration algorithm is plugged for purposes of rewarding the recipients for the choice of policies they adhere or fail to adhere to while accessing the possible data units.
Performance Testing in A Multi Tenant Cloud Architecture using Genetic Algorithm

Recent researches in cloud discusses about the application response testing, performance testing, security testing and many more, but still there is a lack of researches addressing issues like resource utilization and user interactions in cloud SaaS testing. The load on the cloud, SaaS instance keeps varying dynamically with respect to time, it is difficult to find the exact load at a particular interval of time. One does not know where to look for the solution and where to start, this made SaaS instances non deterministic in nature. In order to find a solution for such non deterministic problems, we make use of Genetic Algorithm which is considered as a good solution for non-deterministic problems.We determine the optimized resources that a cloud instance, would need to manage the dynamic load at all times. Toaddress the resource utilization of a group of users in MultiTenant Architecture (MTA), we adopt Genetic Algorithm which uses a popular technique, called neighborhood search and instance ranking policy. The basic concept of this paper is to explore the neighbors of an existing solution, that is considered as the solutions which can be obtained with a specific operation on the base population. In addition to that,this paper discusses about the ranking of all the available population and select the most highly ranked one. Instance ranking policies are aimed at minimizing the number of nodes in use or maximize the resources available to each node in an instance.