An important problem in molecular biology is to predict the secondary structure of proteins from their primary structure. The primary structure of a protein is the sequence of amino acid residues. The secondary structu ...

Concurrent error detection (CED) is the detection of errors or faults in a circuit or data path concurrent with normal operation of that circuit. The general approach for CED is to calculate a check symbol for the inpu ...

Spreadsheets are a widely used end-user programming tool. Field audits have found that 80-90% of spreadsheets created by end users contain textual and formula errors in spreadsheets. Such errors may have severe negative ...

Error correction codes (ECCs) have been widely used in communication systems and storage devices. Nowadays, the rapid development of integrated circuit technologies makes feasible the implementation of powerful ECCs such ...

The asymmetric nature of bit errors in several practical applications provides grounds for efficient error control techniques. The Z-channel model and special classes of codes like asymmetric error detection codes and ...

Today's computer and network communication systems rely on authenticated and secure transmission of information, which requires computationally efficient and low bandwidth cryptographic algorithms. Among these cryptogr ...

We present a catalog of mutation operators for spreadsheets drawn from research into mutation testing for general purpose programming languages and from spreadsheet errors that have been reported in literature. These ope ...

Markov models are commonly used for joint inference of label sequences. Unfortunately, inference scales quadratically in the number of labels, which is problematic for training methods where inference is repeatedly prefo ...

In some practical systems, most of the errors are of 1 → 0 type and 0 → 1 errors occur very rarely. In this thesis, first, the capacity of the asymmetric channel is derived. The capacity of the binary symmetric channel ...

Error-correcting output coding (ECOC) is a method for converting a k-class supervised learning problem into a large number L of two-class supervised learning problems and then combining the results of these L evaluatio ...