This paper presents the coupling of a building thermal simulation code with genetic algorithms (GAs). GAs are randomized search algorithms that are based on the mechanisms of natural selection and genetics. We show that this coupling allows the location of defective sub-models of a building thermal model i.e. parts of model that are responsible for the disagreements between measurements and mod...

In this paper, we propose a novel method to construct low rate recursive convolutional codes. The ‘overall’ convolutional code has a block code and a simple recursive convolutional code as building blocks. The novelty of this type of convolutional code is that it uses coset leaders in order to distinguish the signals that originate from different states. Several of these codes are then used to ...

Code composition is an effective technique for a compiler to implement complex high-level operations. The developer (i.e., the language designer or compiler writer) provides building blocks consisting of sequences of code written in, e.g., C, that are combined by a composition system to generate the code for such a high-level operation. The composition system can include optimizations not commo...

We estimate the resource requirements for the quantum simulation of the ground-state energy of the onedimensional quantum transverse Ising model based on the surface code implementation of a fault-tolerant quantum computer. The surface code approach has one of the highest known tolerable error rates (∼1%) which makes it currently one of the most practical quantum computing schemes. Compared to ...

In this paper we use the Gray code representation of the genetic code C=00, U=10, G=11 and A=01 (C pairs with G, A pairs with U) to generate a sequence of genetic code-based matrices. In connection with these code-based matrices, we use the Hamming distance to generate a sequence of numerical matrices. We then further investigate the properties of the numerical matrices and show that they are d...

Two key contributions presented in this paper are: i) A method for building a dataset containing source code features extracted from source files taken from Open Source Software (OSS) and associated bug reports, ii) A predictive model for estimating defectiveness of a given source code. These artifacts can be useful for building tools and techniques pertaining to several automated software engi...