Performance of sharing real-time snapshot

Meteor on täyden pinon web-sovelluskehys, joka on omiaan yhteisöllisesti tuotetun informaation jakamiseen reaaliaikaisesti käyttäjiensä kesken. Työn tavoitteena oli tutkia jo valmiiksi aloitetun Meteor-pohjaisen tilannekuvasovelluksen suorituskykyongelmia ja ratkaista niitä käyttäen tekniikoita, joilla työ oli jo aloitettu tai joita on mahdollista liittää siihen ilman suurempia ongelmia. Toissijaisesti työssä oli tarkoitus tutkia vaihtoehtoisia web-tekniikoita, joiden avulla suorituskykyä voidaan parantaa. Tilannekuvasovelluksessa osallistuvat henkilöt liikuttavat hallinnoimiaan objekteja ja välittävät objektiensa liikkeen reaaliaikaisesti toisilleen niin, että kukin osallistuja näkee reaaliaikaisena objektien sijainnin ja suunnan kertovan tilannekuvan, jossa objektit liikkuvat nykimättä ruudulla. Keskeisenä ongelmana tilannekuvasovelluksessa olivat tilannekuvan välittämiseen ja esittämiseen liittyvät viiveet. Nämä asettavat haasteita sille, että käyttäjä kokee käyttöliittymän reagoivan nopeasti tehtyihin muutoksiin, ja sille, että osallistujien näkymät ovat yhdenmukaisia. Työssä perehdyttiin renderöinnin ja kommunikaation taustalla oleviin web-tekniikoihin ja niiden suorituskykyyn. Riittävä reaaliaikaisuus tilannekuvasovelluksessa saavutettiin ohittamalla paikkaviestien välittäminen MongoDB-tietokannan kautta käyttämällä vain viestipalvelimen välimuistia ja koostamalla välitettäviä viestejä palvelinpäässä tietyllä aikavälillä, jolloin välitettävien viestien määrä olennaisesti väheni. Suorituskyvyn parantamiseksi mahdollisina kehityssuuntina evaluoitiin myös CSS3-, SVG-, canvas- ja WebGL-piirtotekniikoiden käyttöä eri mobiililaitealustoilla: testeissä WebGL oli yksiselitteisesti nopein, muilla menetelmillä tulokset olivat ristiriitaisia eri laitealustoilla

Performance Challenges with Data Visualizations in Browser Environment

Information exists in many forms, from text, to equations, videos, audio, and graphical mediums. With graphical or visual mediums, it is becoming easier to absorb information where the alternatives are textual descriptions. Graphs are important vehicles of transporting information. In order to create a good graph, certain attributes need to be taken into account, such as which variables are being displayed over which axis, visual elements, and their sizes are also important to consider. In modern times with the internet and the amount of data being generated, how can all this data be fitted into a single graph? That question is the motivation for this thesis. Presenting large data in visualizations involves a great deal of thought, effort, and ingenuity on how to proceed with what information to convey. There are times when obtaining data for such visualization come with their own challenges. This thesis investigates the obstacles facing an internal tool within a company in regard to their data retrieval method. As well as the objective to research an efficient and easy-to-use method for presenting large data on a webpage

Benefits and pitfalls of using HTML5 APIs for online experiments and simulations

The most recent advances in the architecture of the Web allow using it as an excellent platform to deliver experiments and simulations over the Internet. However, there are still some challenges related to the animations' accuracy, to user input collection or to real-time communications that have to be accomplished to properly port native application- based experiments and simulations to the Web. The limitations of the standards preceding HTML5 have forced web developers to embed non-HTML objects using a wide range of non-standard plugins and causing an extremely fragmented execution environment where features must be implemented several times in different programming languages to guarantee full compliance with every user-agent. As HTML5 provides a standard -yet fully-featured- environment to develop and execute applications, web user-agents are now more similar to application players than to simple Internet browsers. In this paper we analyze the benefits and pitfalls of these new Application Programming Interfaces (APIs), providing examples of both good and bad instances of research-related use

Desenvolvimento de laboratório de experimentação remota didático para aprendizagem na área da conformação mecânica

Esta tese trata do desenvolvimento de um laboratório remoto didático para estudos na área da Conformação Mecânica, chamado de Laboratório Online de Conformação Mecânica (LABCONM), o qual visa proporcionar a aprendizagem da Conformação Mecânica usando experimentos reais operados remotamente. Este laboratório é formado por duas partes principais: A primeira parte é um Sistema de Gerenciamento de Aprendizagem (SGA) contendo todos os menus, atividades e tarefas, agenda e painel de acesso e controle aos experimentos. A segunda parte é a parte física, ou seja, o experimento remoto, que nesta primeira versão do LABCONM é a “Máquina Didática Teleoperada de Ensaio de Compressão” (MDTEC). No painel de controle da MDTEC o estudante controla e visualiza remotamente um ensaio de compressão real e exporta os dados. Uma atividade de aprendizagem experimental foi desenvolvida para guiar os estudantes na busca da solução do problema, gerando assim a aprendizagem da curva de escoamento. Para validar o laboratório, foram feitos dois tipos de testes: O primeiro é funcional e técnico, que analisa os resultados do experimento remoto, avaliando a similaridade e a repetibilidade para fins didáticos. E o segundo teste é uma validação acadêmica, que foi dividida em duas partes. A primeira, foi direta, e feita por um grupo de estudantes da disciplina de Conformação Mecânica, onde responderam questionários após uso do laboratório. A segunda etapa foi indireta, feita pela comparação das notas da prova entre os estudantes que "usaram" com aqueles que "não usaram" o laboratório, visando obter a influência do uso do laboratório na aprendizagem. Os resultados dos testes técnicos e funcionais mostram que a MDTEC é um experimento que tem condições de realizar ensaios de compressão reais, fornecendo dados com boa repetibilidade para levantamento de curvas de escoamento. Na avaliação dos estudantes o LABCONM demonstrou ter cumprido com o objetivo de ensino aprendizagem. Em relação à avaliação da prova aplicada com ambos os grupos de estudantes com e sem acesso ao LABCONM, observou-se que houve uma influencia positiva nos resultados da turma que acessou o laboratório, visto que nenhum destes estudantes do grupo teve nota insatisfatória no exercício de cálculo.This thesis deals with the development of a remote didactic laboratory for studies in the area of Metal Forming, called the Online Laboratory of Metal Forming (LABCONM), which aims to provide the learning of the Metal Forming using real remotely operated experiments. This lab consists of two main parts: The first part is a Learning Management System (SGA) containing all the menus, activities and tasks, agenda and access panel and control to the experiments. The second part is the physical part, that is, the remote experiment, which in this first version of LABCONM is the "Teleoperated Testing Machine for Compression Testing" (MDTEC). In the MDTEC control panel the student remotely controls and visualizes a real compression test and exports the data. An experimental learning activity was developed to guide the students in the search of the solution of the problem, thus generating learning the flow curve. To validate the laboratory, two types of tests were performed: The first one is functional and technical, which analyzes the results of the remote experiment, evaluating similarity and repeatability for didactic purposes. And the second test is an academic validation, which was divided into two parts. The first one was direct, and made by a group of students of the discipline of Mechanical Conformation, where they answered questionnaires after using the laboratory. The second stage was indirect, made by comparing test scores among students who "used" those who "did not use" the laboratory, in order to obtain the influence of the use of the laboratory in learning. The results of the technical and functional tests show that the MDTEC is an experiment that is able to perform real compression tests, providing data with good repeatability for survey of flow curves. In the evaluation of the students the LABCONM has demonstrated to have fulfilled with the objective of teaching-learning. Regarding the evaluation of the test applied with both groups of students with and without access to LABCONM, it was observed that there was a positive influence on the results of the group that visited the laboratory, since none of these students of the group had an unsatisfactory grade in the calculation

Enabling peer-to-peer remote experimentation in distributed online remote laboratories

Remote Access Laboratories (RALs) are online platforms that allow human user interaction with physical instruments over the Internet. Usually RALs follow a client-server paradigm. Dedicated providers create and maintain experiments and corresponding educational content. In contrast, this dissertation focuses on a Peer-to-Peer (P2P) service model for RALs where users are encouraged to host experiments at their location. This approach can be seen as an example of an Internet of Things (IoT) system. A set of smart devices work together providing a cyber-physical interface for users to run experiments remotely via the Internet. The majority of traditional RAL learning activities focus on undergraduate education where hands-on experience such as building experiments, is not a major focus. In contrast this work is motivated by the need to improve Science, Technology, Engineering and Mathematics (STEM) education for school-aged children. Here physically constructing experiments forms a substantial part of the learning experience. In the proposed approach, experiments can be designed with relatively simple components such as LEGO Mindstorms or Arduinos. The user interface can be programed using SNAP!, a graphical programming tool. While the motivation for the work is educational in nature, this thesis focuses on the technical details of experiment control in an opportunistic distributed environment. P2P RAL aims to enable any two random participants in the system - one in the role of maker creating and hosting an experiment and one in the role of learner using the experiment - to establish a communication session during which the learner runs the remote experiment through the Internet without requiring a centralized experiment or service provider. The makers need to have support to create the experiment according to a common web based programing interface. Thus, the P2P approach of RALs requires an architecture that provides a set of heterogeneous tools which can be used by makers to create a wide variety of experiments. The core contribution of this dissertation is an automaton-based model (twin finite state automata) of the controller units and the controller interface of an experiment. This enables the creation of experiments based on a common platform, both in terms of software and hardware. This architecture enables further development of algorithms for evaluating and supporting the performance of users which is demonstrated through a number of algorithms. It can also ensure the safety of instruments with intelligent tools. The proposed network architecture for P2P RALs is designed to minimise latency to improve user satisfaction and learning experience. As experiment availability is limited for this approach of RALs, novel scheduling strategies are proposed. Each of these contributions has been validated through either simulations, e.g. in case of network architecture and scheduling, or test-bed implementations, in case of the intelligent tools. Three example experiments are discussed along with users' feedback on their experience of creating an experiment and using others’ experimental setup. The focus of the thesis is mainly on the design and hosting of experiments and ensuring user accessibility to them. The main contributions of this thesis are in regards to machine learning and data mining techniques applied to IoT systems in order to realize the P2P RALs system. This research has shown that a P2P architecture of RALs can provide a wide variety of experimental setups in a modular environment with high scalability. It can potentially enhance the user-learning experience while aiding the makers of experiments. It presents new aspects of learning analytics mechanisms to monitor and support users while running experiments, thus lending itself to further research. The proposed mathematical models are also applicable to other Internet of Things applications