Hardware-accelerated interactive data visualization for neuroscience in Python.

Large datasets are becoming more and more common in science, particularly in neuroscience where experimental techniques are rapidly evolving. Obtaining interpretable results from raw data can sometimes be done automatically; however, there are numerous situations where there is a need, at all processing stages, to visualize the data in an interactive way. This enables the scientist to gain intuition, discover unexpected patterns, and find guidance about subsequent analysis steps. Existing visualization tools mostly focus on static publication-quality figures and do not support interactive visualization of large datasets. While working on Python software for visualization of neurophysiological data, we developed techniques to leverage the computational power of modern graphics cards for high-performance interactive data visualization. We were able to achieve very high performance despite the interpreted and dynamic nature of Python, by using state-of-the-art, fast libraries such as NumPy, PyOpenGL, and PyTables. We present applications of these methods to visualization of neurophysiological data. We believe our tools will be useful in a broad range of domains, in neuroscience and beyond, where there is an increasing need for scalable and fast interactive visualization

Implementation of an OpenVG Rasterizer with Configurable Anti-aliasing and Multi-window Scissoring

This paper describes an OpenVG-compliant hardware rasterizer with configurable anti-aliasing and multi-window scissoring. This rasterizer requires 129K logic gates with 2KB on-chip SRAM and provides satisfactory image quality with a reasonable rasterizer speed at the operational frequency of 100MHz. In this paper, we propose an optimized scanline algorithm, which provides better performance than the conventional scanline algorithm with supersampline while maintaining the flexibility and the hardware simplicity. We also propose a fast LUT-based scissoring algorithm, which has zero-latency in most of the cases. The hardware implementation of this rasterizer is explained in detail

Machine to Machine Communication for Health Care and Disaster Management

Machine to Machine communication for health and disaster management aims to develop a software module that will take data from the pulse or heart rate and temperature of a human being. The two machines involved here are a Raspberry pi and the own Personal Computer of the patient. The measured data is sent to one monitoring device via LAN as digital data and the samples will be analysed for a threshold level. If it exceeds it then person will not be allowed to drive the vehicle for these results will be compared with the parameters of a human body after alcohol consumption. This incorporates medical and disaster applications both. The video conferencing module is added so as to provide a direct communication between patient and health care professional. The data can be sent to medical professionals at the back end and the person can be warned of the health hazards as well as incorporating this will regulate and reduce the number of road accidents that take place due to reckless and drunk drivin

The control and data transfer system of the automated hydrometeorological / environmental station of the theorems-dnipro international project

Материалы XVIII Междунар. науч.-техн. конф. студентов, аспирантов и молодых ученых, Гомель, 26–27 апр. 2018 г

Modelling and Optimization of Data-Driven Scene Graphs

International audienceThis article presents data-driven scene graphs, a set of models that address the needs of safety-critical user interfaces design. Data-driven scene graphs merge a description of the user interface behavior as a data-flow program with a description of its graphics content as a hierarchical structure of vector and raster elements. We present a formal description of these models, discuss their semantics and equivalence, and demonstrate that they are suitable for a class of rasterization optimizations based on selective pre-rendering

Graafisen etäkäyttöliittymän kehittäminen Raspberry Pi:lle

Tämän insinöörityön toimeksiantaja oli KajaPro Oy, ja työ tuli yrityksen omaan käyttöön. Työn tarkoituksena oli kehittää KajaPro Oy:n graafinen etäkäyttöliittymä Raspberry Pi -sulautetulle laitteelle. Ohjelmistotuotteen kehittämisen vaatimuksena oli, että ohjelmakoodi voidaan kääntää Windows 7 -käyttöjärjestelmästä Raspbian wheezy -käyttöjärjestelmään, jota käytetään Raspberry Pi -laitteen käyttöjärjestelmänä. Lisäksi tällä laitteella piti testata socket-tietoliikenneyhteys. Graafiseen etäkäyttöliittymään piti myös suunnitella ja toteuttaa joystick-komponentti, jota voidaan hyödyntää servomoottoreiden ohjauksessa. Insinöörityön toteuttamiseen käytettiin KajaPro Oy:n graafista etäkäyttöliittymää, jonka resursseja hyödyntäen joystick-komponentti suunniteltiin ja toteutettiin. Komponenttia, jonka avulla ohjattiin servomoottoreita, testattiin Android-käyttöjärjestelmän sisältävässä mobiililaitteessa. Ohjelmistokehitysympäristönä käytettiin Microsoft Visual Studio 2010 -ohjelmaa. Insinöörityö alkoi joystick-komponentin suunnittelulla ja komponentin toiminnan ohjelmoinnilla C++-ohjelmointikielellä. Ristikääntäjää varten täytyi tehdä tutkimustyötä siitä, kuinka ohjelmakoodi saadaan käännettyä toiselta laitteistoarkkitehtuurilta toiselle. Kääntäjä, joka sisältää GNU-projektin työkaluja, asennettiin Windows 7 -ympäristöön. Raspberry Pi tarvitsee EGL-rajapintaa grafiikan esittämiseen ja SDL-rajapintaa näppäimistön ja hiiren toiminnallisuuteen. Kääntäjä tarvitsee useita kirjastoja, jotka pitävät sisällään EGL-, OpenGL ES 2- ja SDL-koodien metodit. Nämä kirjastot piti konfiguroida ja kääntää Raspberry Pi:llä ja siirtää Windows 7:lle. Kirjastojen täytyy olla linkitettynä linkkerin avulla, jotta kääntäjä löytää ohjelmakoodin tarvitsemat toiminnallisuudet. KajaPro Oy:n graafinen etäkäyttöliittymä voidaan kääntää Raspberry Pi:lle, kun kehitysympäristö on saatu kokoon. Ristikääntäjä, joka kääntää ohjelmistotuotteen koodin suoritettavaksi tiedostoksi, toteutettiin tätä varten. Suoritettava tiedosto voidaan käynnistää vain Raspbian wheezy -käyttöjärjestelmällä. Tämän insinöörityön lopputulos oli onnistunut. Ristikääntäjä kääntää ohjelmakoodin haluttuun muotoon ja KajaPro Oy:n ohjelmistotuote käynnistyy Raspberry Pi:llä. Socket-tietoliikenneyhteyttä testattiin kahden eri Raspberry Pi:n avulla ja serveriltä lähetetty graafinen käyttöliittymä saapui perille molemmille laitteille. Tämä insinöörityö on hyödyllinen niille, jotka tarvitsevat tietoa, kuinka lähdekoodi voidaan kääntää Windows 7 -ympäristöstä Raspbian wheezy -ympäristöön.This Bachelor´s thesis was commissioned by KajaPro Oy and was made for the sole use of the company. The purpose of work was to develop the company´s remote graphical user interface to Raspberry Pi embedded device. The development of the software demanded that the program code could be compiled from Windows 7 to Raspbian wheezy, which is in this case the operating system of the embedded device. A socket data communication had to be tested in the embedded system. Also, a joystick component had to be designed and made programmatically to the software of the company. The thesis started by programming the joystick component with programming language C++. The application that was used in writing the code was Microsoft Visual Studio 2010. The socket data communication was tested with Hercules utility in Windows 7. Research work had to be done in order to know how to compile code from different software architecture to another. The compiler which uses GNU is Not Unix (GNU) project toolchain was installed to the development environment. Raspberry Pi needs Interface between Khronos Group rendering (EGL) to show graphics and Simple DirectMedia Layer (SDL) to understand keyboard and mouse functionalities in the system. The compiler needs several libraries which hold the methods to the Open Graphics Layer for Embedded Systems 2 (OpenGL ES 2) and SDL. These interfaces had to be configured and built in the embedded device and then moved to the target operating system. There they had to be included and linked against in order to the compiler to find the required functions. The result of this thesis was successful. After the development environment was established the source code of the company could be compiled to the operating system needed. The cross-compiler compiles the code to an executable file and the software of KajaPro Oy runs in Raspberry Pi. The socket data communication was tested with two of these embedded systems and the graphical user interface from server was received in both devices. This thesis is useful for those who need to know how to compile code from Windows 7 environment to Raspbian wheezy environment

Remote Video Monitoring System Using Raspberry Pi 3 and GPRS Module

Now a day’s security has prime importance in different areas such as home security, monitoring of remote areas etc. with advancement in embedded system and wireless technology, it is possible to build a remote area monitoring system with low cost. This paper represents a system implemented by using Raspberry Pi 3 and GPRS module. Transmitter section is implemented at remote area where images are captured by using USB camera interfaced with Raspberry pi. Images are compressed by software programming using libjpeg library and uploaded to HTTP server via SIM900A/800 GSM/GPRS module. Internet connection is established using PPP stack of SIM900A/800 GSM/GPRS module. Receiver section is monitoring center where images are downloaded using 3g or Wi-Fi wireless connection. Received images are decompressed and streamed on web browser using MJPG streamer