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BCI Software
Published in Chang S. Nam, Anton Nijholt, Fabien Lotte, Brain–Computer Interfaces Handbook, 2018
LabVIEW (Laboratory Virtual Instrument Engineering Workbench) is a commercial graphical block programming interface software for data acquisition, signal processing, visualization, and controlling of instrumentation. The most recent version of LabVIEW (2016) runs on Windows 7, 8.1, and 10 and, with limited functionality, on Mac OS X (10.10, 10.11) and Linux (Red Hat, Scientific, openSUSE). National Instruments has been developing LabVIEW since 1983, mainly to serve as a real-time processing frontend for their NI-DAQ (Data Acquisition) series hardware. This type of hardware provides affordable analog and digital input/output at relatively high sampling rates (e.g., 100 kHz) and resolution (e.g., ±500 mV dynamic range, 3 μV resolution at 16 bits). In combination with appropriate pre-amplifiers, NI-DAQ hardware is suitable for a wide range of biosignal applications. While these boards lack regulatory approval for clinical use in humans, their affordable price (e.g., 1/10th of a comparable biosignal acquisition system approved for human use) made them popular with animal experiments. The ability to interface with external instrumentation through analog and digital NI-DAQ board inputs and outputs, together with an increased availability of data acquisition modules for third-party biosignal acquisition systems (e.g., g.HIsys, g.tec, Austria2; OpenEEG3; OpenBCI4), has led to some adoption of LabVIEW within the BCI community. In this context, LabVIEW has been the basis for several BCI demonstrations that range from EMG-based assistive technology (Huang et al. 2006), to NIRS-based communication (Matthew et al. 2008), to steady-state visual evoked potential (SSVEP)–based wheelchair control (Singla et al. 2014). In addition to these demonstrations, LabVIEW has been used to implement the BCI system Craniux (Degenhart et al. 2011), which is illustrated in Figures 17.5 and 17.6. Craniux has been used for BCI studies in monkeys and for humans with tetraplegia (Wang et al. 2013; Collinger et al. 2013, 2014).
A new interior-point approach for large separable convex quadratic two-stage stochastic problems
Published in Optimization Methods and Software, 2022
Jordi Castro, Paula de la Lama-Zubirán
For testing the performance of the proposed specialized interior-point method, an initial comparison was made using the state-of-the-art IBM ILOG CPLEX (v. 12.7) barrier optimizer. Unlike BlockIP, CPLEX computes directions by direct solvers, instead of a combination of Cholesky and PCG. CPLEX executions were made without crossover for a fair comparison with BlockIP. In this preliminary experiments, for BlockIP the problems were modelled using the splitting formulation (7), whereas for CPLEX the dual of the extensive form (3) was used, in an attempt to avoid dense columns due to the first-stage variables. All the experiments in this work were carried out on a Fujitsu Primergy RX2540 M1 4X server with two 2.6 GHz Intel Xeon E5-2690v3 CPUs (48 cores) and 192 Gigabytes of RAM, under a GNU/Linux operating system (openSuse 13.2), without exploitation of multithreading capabilities.
Iterated local and very-large-scale neighborhood search for a novel uncapacitated exam scheduling model
Published in International Journal of Management Science and Engineering Management, 2018
Salim Haddadi, Meryem Cheraitia
The proposed method is coded in C on Linux OS (openSUSE 13.1) and run on an Intel®Core™I3 (2.4 GHz). The code is tested on the University of Toronto benchmark data set (Carter et al., 1996; Qu et al., 2009), which consists of twelve instances freely available from the website http://www.cs.nott.ac.uk/~pszrq/data.htm. The characteristics of the instances are presented in Table 1. The first column gives the instance name. Columns two and three display the number n of exams and m of students. Columns four and five provide the density (as a percentage) of the conflict matrix and the number p of allowed periods.
A detailed description of methyl methacrylate free radical polymerization using different heating policies under isothermal and non-isothermal conditions: a kinetic Monte Carlo simulation
Published in International Journal of Modelling and Simulation, 2021
Ramin Bairami Habashi, Mohammad Najafi, Peyman Mostafaei, Behrouz Shojaei
The simulation code is written in C++ language and compiled into 64-bit executable code using GCC (GNU Compiler Collection) version 7.3.1. The average runtime of the program at a simulation volume of 10−12 on a desktop computer equipped with Intel Core i7-3770K (3.50 GHz) and 32 GB of memory (2133 MHz) running openSUSE Leap 15.0 × 64 operating system is approximately 30 min.