Static software checking tools are useful as an additional automated software inspection step that can easily be integrated in the development cycle and assist in creating secure, reliable and high quality code. However, an often quoted disadvantage of these tools is that they generate an inordinate number of warnings, including many false positives due to the use of approximate analysis techni...

Approximate string matching (ASM) is a well-known computational problem with important applications in database searching, plagiarism detection, spelling correction, and bioinformatics. The two main issues with most ASM algorithms are (1) computational complexity, and (2) low specificity due to a large amount of false positives being reported. In this paper, a very efficient ASM method is propo...

Simplified model binding sites allow one to isolate entangled terms in molecular energy functions. Here, we investigate the effects on ligand recognition of the introduction of a histidine into a hydrophobic cavity in lysozyme. We docked 656040 molecules and tested 26 highly and nine poorly ranked. Twenty-one highly ranked molecules bound and five were false positives, while three poorly ranked...

Knowledge of all molecular interactions that potentially take place in the cell is a key for a detailed understanding of cellular processes. Currently available interaction data, such as protein-protein interaction maps, are known to contain false positives that inevitably diminish the accuracy of network-based inferences. Interaction confidence scoring is thus a crucial intermediate step after...

New ELISAs for detecting macroamylase or free autoantibodies to amylase were tested with 48 samples that had been characterized by gel chromatography and electrophoresis. The macroamylase ELISA, with anti-IgG or anti-IgA for detection, detected macroamylase in 28 of 33 samples known to contain macroamylase (85% sensitivity), whereas the ELISA for free autoantibody to amylase was positive for on...

We investigate nonadaptive group testing designs for heterogeneous mixtures of objects, independently positive with individual prior probabilities. In our model of the prior probabilities, the objects occur in one of several disjoint subsets and the number of positives in each subset is known. Furthermore, the positives are “uniformly distributed” within the subsets. The expected number of unre...

A total of 429 specimens belonging to 9 species of small mammals, trapped in various areas of the Czech Republic during the year 2001, were examined for antibodies against leptospires. Antibodies were found in all localities under study in 50 specimens, i.e., 11.6%, belonging to 5 species. Antibodies were most often , i.e., in 42% of positives, found in Microtus arvalis. In Apodemus spp. and Cl...

In the network security domain Intrusion detection systems (IDS) are known for their problems in creating huge amounts of data and especially false positives. Several approaches, originating in the machine learning domain, have been proposed for a better classification. However, threat prioritization has also shown, that a distinction in true and false positives is not always sufficient for a p...

Modern concurrent software is riddled with data races and these races constitute the source of many problems. Data races are hard to detect accurately before software is shipped and, once they cause failures in production, developers find it challenging to reproduce and debug them. Ideally, all data races should be known before software ships. Static data race detectors are fast, have few false...

Cloud services delivered as utility computing over the Internet makes it an attractive target for cyber intruders. Protecting network accessible Cloud resources and services from ever increasing cyber threats is of great concern. Most of the Network based Intrusion Detection System (NIDS) being rule based and therefore only capable of identifying known attacks (through pattern matching). Tradit...