Search results for "CODE"
showing 10 items of 1180 documents
Code Contracts ja ComTest-yksikkötestausgenerointi .NET-kielissä
2015
Opetuksen tehostamiseen suunnattu työkalu ComTest osaa luoda yksikkötestejä koodin kommentteihin kirjoitettujen ohjeiden perusteella. Sopimuspohjaisessa suunnittelussa olion metodeille asetetaan ehtoja, joiden on oltava voimassa ennen operaation suorittamista tai sen jälkeen. Tällaiset ehdot voidaan automaattisesti kirjoittaa osaksi koodin kommentteja. Code Contracts on laajennos .NET-kieliin, jonka avulla sopimuspohjainen suunnittelu saadaan osaksi sovelluskehitystä. Tutkimuksessa selvitetään, miten ComTest ja Code Contracts liittyvät toisiinsa. ComTest, a tool mainly directed to make teaching more efficient, is able to create Unit Tests based on directions written in the code comments. In…
Efficient generation of restricted growth words
2013
A length n restricted growth word is a word w=w"1w"2...w"n over the set of integers where w"1=0 and each w"i, i>1, lies between 0 and the value of a word statistics of the prefix w"1w"2...w"i"-"1 of w, plus one. Restricted growth words simultaneously generalize combinatorial objects as restricted growth functions, staircase words and ascent or binary sequences. Here we give a generic generating algorithm for restricted growth words. It produces a Gray code and runs in constant average time provided that the corresponding statistics has some local properties.
Restricted compositions and permutations: from old to new Gray codes
2011
Any Gray code for a set of combinatorial objects defines a total order relation on this set: x is less than y if and only if y occurs after x in the Gray code list. Let @? denote the order relation induced by the classical Gray code for the product set (the natural extension of the Binary Reflected Gray Code to k-ary tuples). The restriction of @? to the set of compositions and bounded compositions gives known Gray codes for those sets. Here we show that @? restricted to the set of bounded compositions of an interval yields still a Gray code. An n-composition of an interval is an n-tuple of integers whose sum lies between two integers; and the set of bounded n-compositions of an interval si…
SiC MOSFET vs SiC/Si Cascode short circuit robustness benchmark
2019
Abstract Nowadays, MOSFET SiC semiconductors short circuit capability is a key issue. SiC/Si Cascodes are compound semiconductors that, in some aspects, show a similar MOSFET behaviour. No interlayer dielectric insulation suggests, in theory, Cascode JFETs as more robust devices. The purpose of this paper is to compare the drift and degradation of two commercial devices static parameters by exposing them to different levels of repetitive 1.5 μs short-circuit campaigns at 85% of its breakdown voltage. Short-circuit time has been set experimentally, and longer times result in catastrophic failure of MOSFET devices due to over self-heating. For this purpose, pre- and post-test short circuit ch…
THE GYROTRON STARTUP SCENARIO IN THE SINGLE MODE TIME DEPENDENT APPROACH
2019
The paper explains how to solve the Gyrotron equation system in the Single Mode Time Dependent Approach. In particular, we point out problems encountered when solving these well-known equations. The starting current estimation approach a using time model is suggested. The solution has been implemented in the Matlab code, which is attached to the article.
Online Management of Hybrid DRAM-NVMM Memory for HPC
2019
Non-volatile main memories (NVMMs) offer a comparable performance to DRAM, while requiring lower static power consumption and enabling higher densities. NVMM therefore can provide opportunities for improving both energy efficiency and costs of main memory. Previous hybrid main memory management approaches for HPC either do not consider the unique characteristics of NVMMs, depend on high profiling costs, or need source code modifications. In this paper, we investigate HPC applications' behaviors in the presence of NVMM as part of the main memory. By performing a comprehensive study of HPC applications and based on several key observations, we propose an online hybrid memory architecture for …
Data-driven Fault Diagnosis of Induction Motors Using a Stacked Autoencoder Network
2019
Current signatures from an induction motor are normally used to detect anomalies in the condition of the motor based on signal processing techniques. However, false alarms might occur if using signal processing analysis alone since missing frequencies associated with faults in spectral analyses does not guarantee that a motor is fully healthy. To enhance fault diagnosis performance, this paper proposes a machinelearning based method using in-built motor currents to detect common faults in induction motors, namely inter-turn stator winding-, bearing- and broken rotor bar faults. This approach utilizes single-phase current data, being pre-processed using Welch’s method for spectral density es…
Joint Gaussian processes for inverse modeling
2017
Solving inverse problems is central in geosciences and remote sensing. Very often a mechanistic physical model of the system exists that solves the forward problem. Inverting the implied radiative transfer model (RTM) equations numerically implies, however, challenging and computationally demanding problems. Statistical models tackle the inverse problem and predict the biophysical parameter of interest from radiance data, exploiting either in situ data or simulated data from an RTM. We introduce a novel nonlinear and nonparametric statistical inversion model which incorporates both real observations and RTM-simulated data. The proposed Joint Gaussian Process (JGP) provides a solid framework…
Optimal modalities for radiative transfer-neural network estimation of canopy biophysical characteristics: Evaluation over an agricultural area with …
2011
International audience; Neural networks trained over radiative transfer simulations constitute the basis of several operational algorithms to estimate canopy biophysical variables from satellite reflectance measurements. However, only little attention was paid to the training process which has a major impact on retrieval performances. This study focused on the several modalities of the training process within neural network estimation of LAI, FCOVER and FAPAR biophysical variables. Performances were evaluated over both actual experimental observations and model simulations. The SAIL and PROSPECT radiative transfer models were used here to simulate the training and the synthetic test dataset…
Gaussian Processes Retrieval of LAI from Sentinel-2 Top-of-Atmosphere Radiance Data
2020
Abstract Retrieval of vegetation properties from satellite and airborne optical data usually takes place after atmospheric correction, yet it is also possible to develop retrieval algorithms directly from top-of-atmosphere (TOA) radiance data. One of the key vegetation variables that can be retrieved from at-sensor TOA radiance data is leaf area index (LAI) if algorithms account for variability in atmosphere. We demonstrate the feasibility of LAI retrieval from Sentinel-2 (S2) TOA radiance data (L1C product) in a hybrid machine learning framework. To achieve this, the coupled leaf-canopy-atmosphere radiative transfer models PROSAIL-6SV were used to simulate a look-up table (LUT) of TOA radi…