Towards General Purpose, High Level, Software Languages

2005 ◽  
pp. 220-238 ◽  
Author(s):  
Anneke Kleppe
Keyword(s):  
General Purpose ◽  
High Level

scholarly journals SoC-FPGA systems for the acquisition and processing of electroencephalographic signals

2021 ◽  
Vol 10 (3) ◽  
pp. 237
Author(s):  
Matias Javier Oliva ◽  
Pablo Andrés García ◽  
Enrique Mario Spinelli ◽  
Alejandro Luis Veiga
Keyword(s):  
Embedded System ◽  
Real Time ◽  
General Purpose ◽  
System Response ◽  
Single Chip ◽  
Real Time Processing ◽  
General Purpose Processor ◽  
Time Operation ◽  
Electroencephalographic Signals ◽  
High Level

<span lang="EN-US">Real-time acquisition and processing of electroencephalographic signals have promising applications in the implementation of brain-computer interfaces. These devices allow the user to control a device without performing motor actions, and are usually made up of a biopotential acquisition stage and a personal computer (PC). This structure is very flexible and appropriate for research, but for final users it is necessary to migrate to an embedded system, eliminating the PC from the scheme. The strict real-time processing requirements of such systems justify the choice of a system on a chip field-programmable gate arrays (SoC-FPGA) for its implementation. This article proposes a platform for the acquisition and processing of electroencephalographic signals using this type of device, which combines the parallelism and speed capabilities of an FPGA with the simplicity of a general-purpose processor on a single chip. In this scheme, the FPGA is in charge of the real-time operation, acquiring and processing the signals, while the processor solves the high-level tasks, with the interconnection between processing elements solved by buses integrated into the chip. The proposed scheme was used to implement a brain-computer interface based on steady-state visual evoked potentials, which was used to command a speller. The first tests of the system show that a selection time of 5 seconds per command can be achieved. The time delay between the user’s selection and the system response has been estimated at 343 µs.</span>

scholarly journals A Runtime System for XML Transformations in Java

2004 ◽  
Vol 11 (33) ◽  
Author(s):  
Aske Simon Christensen ◽  
Christian Kirkegaard ◽  
Anders Møller
Keyword(s):  
Static Analysis ◽  
Programming Language ◽  
Program Analysis ◽  
Companion Paper ◽  
General Purpose ◽  
Runtime System ◽  
Xml Documents ◽  
Level Data ◽  
High Level ◽  
The Given

We show that it is possible to extend a general-purpose programming language with a convenient high-level data-type for manipulating XML documents while permitting (1) precise static analysis for guaranteeing validity of the constructed XML documents relative to the given DTD schemas, and (2) a runtime system where the operations can be performed efficiently. The system, named Xact, is based on a notion of immutable XML templates and uses XPath for deconstructing documents. A companion paper presents the program analysis; this paper focuses on the efficient runtime representation.

scholarly journals MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation

2019 ◽  
Author(s):  
J-Donald Tournier ◽  
Robert Smith ◽  
David Raffelt ◽  
Rami Tabbara ◽  
Thijs Dhollander ◽  
...  
Keyword(s):  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Image Data ◽  
Data Access ◽  
General Purpose ◽  
Computational Performance ◽  
Cross Platform ◽  
High Level ◽  
New Applications

AbstractMRtrix3 is an open-source, cross-platform software package for medical image processing, analysis and visualization, with a particular emphasis on the investigation of the brain using diffusion MRI. It is implemented using a fast, modular and flexible general-purpose code framework for image data access and manipulation, enabling efficient development of new applications, whilst retaining high computational performance and a consistent command-line interface between applications. In this article, we provide a high-level overview of the features of the MRtrix3 framework and general-purpose image processing applications provided with the software.

scholarly journals OPTIMUM PACKAGING OF MACHINES WHILE DEVELOPING A CROWN UNDER A VERTICAL STEEL TANK FOR OIL STORAGE WITH A VOLUME OF 5000 M3

2020 ◽  
pp. 64-71
Author(s):  
А. С. Семин ◽  
С. И. Вахрушев
Keyword(s):  
General Purpose ◽  
Optimization Criterion ◽  
Dynamic Programming Method ◽  
Network Graph ◽  
Construction Machinery ◽  
Oil Storage ◽  
Steel Tank ◽  
External Conditions ◽  
High Level ◽  
Optimal Set

Строительство зданий и сооружений нефтяного комплекса представляет собой сложный технологический процесс, в состав которого входит производство земляных работ. Строительная техника для производства земляных работ должна соответствовать как техническим характеристикам для выполнения поставленных задач при определенных внешних условиях, так и экономическим показателям. В статье рассматривается вопрос оптимального комплектования строительных машин при разработке котлована под вертикальный стальной резервуар (РВС). Разработана программа для поиска оптимального комплекта машин, в условиях полной определенности. Расчет основан на методе динамического программирования Дейкстры. В качестве критерия оптимизации выбраны приведенные затраты на единицу одного кубометра строительной продукции. Расчет представлен для каждого этапа производства работ. По результат расчета построен сетевой граф с выбором оптимального комплекта машин. Программа расчета выполнена на высокоуровневом языке программирования общего назначения Python. The construction of buildings and structures of the oil complex is a complex technological process, which includes the production of earthworks. Construction machinery for earthworks should comply with both the technical characteristics for the performance of tasks under certain external conditions and economic indicators. The article discusses the question of the optimal acquisition of construction vehicles during the development of a pit for a vertical steel tank (TVS). A program has been developed to search for the optimal set of machines, in conditions of complete certainty. The calculation is based on the Dijkstra dynamic programming method. As an optimization criterion, the reduced costs per unit of one cubic meter of construction products were selected. The calculation is presented for each stage of the work. Based on the calculation result, a network graph was constructed with the choice of the optimal set of machines. The calculation program is executed in a high-level general-purpose programming language Python.

Parametric Generator for Architectural and Urban 3D Objects

2013 ◽  
pp. 260-267
Author(s):  
Renato Saleri Lunazzi
Keyword(s):  
Finite Elements ◽  
Conceptual Model ◽  
Geometric Modeling ◽  
General Purpose ◽  
Semantic Description ◽  
3D Objects ◽  
Future Developments ◽  
Simple Tool ◽  
Parametric Generator ◽  
High Level

The authors developed and finalized a specific tool able to model the global structure of architectural objects through a morphological and semantic description of its finite elements. This discrete conceptual model - still in study - was refined during the geometric modeling of the “Vieux Lyon” district, containing a high level of morpho-stylistic disparity. Future developments should allow increasing the genericity of its descriptive efficiency, permitting even more sparse morphological and\or stylistic varieties. Its general purpose doesn’t consist in creating a “universal modeler,” but to offer a simple tool able to quickly describe a majority of standard architectural objects compliant with some standard parametric definition rules.

scholarly journals Machine Learning in Python: Main Developments and Technology Trends in Data Science, Machine Learning, and Artificial Intelligence

Information ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 193 ◽  
Author(s):  
Sebastian Raschka ◽  
Joshua Patterson ◽  
Corey Nolet
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Science ◽  
Gpu Computing ◽  
Graphics Processing Unit ◽  
General Purpose ◽  
Processing Unit ◽  
The Core ◽  
Critical Components ◽  
High Level

Smarter applications are making better use of the insights gleaned from data, having an impact on every industry and research discipline. At the core of this revolution lies the tools and the methods that are driving it, from processing the massive piles of data generated each day to learning from and taking useful action. Deep neural networks, along with advancements in classical machine learning and scalable general-purpose graphics processing unit (GPU) computing, have become critical components of artificial intelligence, enabling many of these astounding breakthroughs and lowering the barrier to adoption. Python continues to be the most preferred language for scientific computing, data science, and machine learning, boosting both performance and productivity by enabling the use of low-level libraries and clean high-level APIs. This survey offers insight into the field of machine learning with Python, taking a tour through important topics to identify some of the core hardware and software paradigms that have enabled it. We cover widely-used libraries and concepts, collected together for holistic comparison, with the goal of educating the reader and driving the field of Python machine learning forward.

scholarly journals Entity deduplication in big data graphs for scholarly communication

2020 ◽  
Vol 54 (4) ◽  
pp. 409-435
Author(s):  
Paolo Manghi ◽  
Claudio Atzori ◽  
Michele De Bonis ◽  
Alessia Bardi
Keyword(s):  
Big Data ◽  
Ground Truth ◽  
Open Science ◽  
General Purpose ◽  
High Level Architecture ◽  
Multiple Sources ◽  
Actual Problem ◽  
Content Type ◽  
Infrastructure System ◽  
High Level

PurposeSeveral online services offer functionalities to access information from “big research graphs” (e.g. Google Scholar, OpenAIRE, Microsoft Academic Graph), which correlate scholarly/scientific communication entities such as publications, authors, datasets, organizations, projects, funders, etc. Depending on the target users, access can vary from search and browse content to the consumption of statistics for monitoring and provision of feedback. Such graphs are populated over time as aggregations of multiple sources and therefore suffer from major entity-duplication problems. Although deduplication of graphs is a known and actual problem, existing solutions are dedicated to specific scenarios, operate on flat collections, local topology-drive challenges and cannot therefore be re-used in other contexts.Design/methodology/approachThis work presents GDup, an integrated, scalable, general-purpose system that can be customized to address deduplication over arbitrary large information graphs. The paper presents its high-level architecture, its implementation as a service used within the OpenAIRE infrastructure system and reports numbers of real-case experiments.FindingsGDup provides the functionalities required to deliver a fully-fledged entity deduplication workflow over a generic input graph. The system offers out-of-the-box Ground Truth management, acquisition of feedback from data curators and algorithms for identifying and merging duplicates, to obtain an output disambiguated graph.Originality/valueTo our knowledge GDup is the only system in the literature that offers an integrated and general-purpose solution for the deduplication graphs, while targeting big data scalability issues. GDup is today one of the key modules of the OpenAIRE infrastructure production system, which monitors Open Science trends on behalf of the European Commission, National funders and institutions.

VRML-Based System for a 3D Virtual Museum

2005 ◽  
pp. 3028-3035
Author(s):  
José-Fernando. Diez-Higuera ◽  
Francisco-Javier Diaz-Pernas
Keyword(s):  
General Purpose ◽  
The Internet ◽  
Web Pages ◽  
Web Browsers ◽  
Static Information ◽  
The World ◽  
Navigation Program ◽  
Long Time ◽  
3D Information ◽  
High Level

In the last few years, because of the increasing growth of the Internet, general-purpose clients have achieved a high level of popularity for static consultation of text and pictures. This is the case of the World Wide Web (i.e., the Web browsers). Using a hypertext system, Web users can select and read in their computers information from all around the world, with no other requirement than an Internet connection and a navigation program. For a long time, the information available on the Internet has been series of written texts and 2D pictures (i.e., static information). This sort of information suited many publications, but it was highly unsatisfactory for others, like those related to objects of art, where real volume, and interactivity with the user, are of great importance. Here, the possibility of including 3D information in Web pages makes real sense.

scholarly journals Robot See Robot Do

2014 ◽  
Vol 136 (09) ◽  
pp. 36-41
Author(s):  
Krishnanand N. Kaipa ◽  
Joshua D. Langsfeld ◽  
Satyandra K. Gupta
Keyword(s):  
General Purpose ◽  
Imitation Learning ◽  
Worcester Polytechnic Institute ◽  
Learning Approaches ◽  
Massachusetts Institute Of Technology ◽  
Federal Institute ◽  
Learning Agent ◽  
Learning From Demonstrations ◽  
Institute Of Technology ◽  
High Level

This article elaborates the concept of programming a robot by showing it how to do the job. This is often called “learning from demonstrations” or “imitation learning.” Labs at several institutions – for example, the Swiss Federal Institute of Technology at Lausanne, the University of Maryland, Massachusetts Institute of Technology, and Worcester Polytechnic Institute – are experimenting with technology that may one day make imitation learning common for machines. The underlying idea of this approach is to allow an agent to acquire the necessary details of how to perform a task by observing another agent (who already has the relevant expertise) perform the same task. Usually, the learning agent is a robot and the teaching agent is a human. Often, the goal of imitation learning approaches is to extract some high-level details about how to perform the task from recorded demonstrations. Research into imitation learning has achieved some impressive results ranging from training unmanned helicopters to perform complex maneuvers to teaching robots general-purpose manipulation tasks.

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