Consistency Checking of the IEC 61508 PFH Formulas and New Formulas Proposal Based on the Markovian Approach

Safety Instrumented Systems (SISs) are of prime importance in protecting people, assets and environment from hazardous events. Therefore, it is important to be able to assess accurately their performance indicators. For this end, IEC 61508 standard has provided two reliability metrics: the average failure probability of a SIS lowly demanded (PFDavg) and the average failure frequency of a SIS highly or continuously demanded (PFH). The aim of this paper is to investigate the IEC 61508 PFH formulas and to propose new ones based on the Markovian approach. Indeed, the new edition of IEC 61508 provides PFH formulas reflecting the possibility of automatic shutdown of the monitored process upon detection of a dangerous failure in the SIS. However, the IEC 61508 attempt remains incomplete and provide non-conservative results, which is dangerous from a safety point of view.

An assertion and alignment correction framework for large scale knowledge bases

Various knowledge bases (KBs) have been constructed via information extraction from encyclopedias, text and tables, as well as alignment of multiple sources. Their usefulness and usability is often limited by quality issues. One common issue is the presence of erroneous assertions and alignments, often caused by lexical or semantic confusion. We study the problem of correcting such assertions and alignments, and present a general correction framework which combines lexical matching, context-aware sub-KB extraction, semantic embedding, soft constraint mining and semantic consistency checking. The framework is evaluated with one set of literal assertions from DBpedia, one set of entity assertions from an enterprise medical KB, and one set of mapping assertions from a music KB constructed by integrating Wikidata, Discogs and MusicBrainz. It has achieved promising results, with a correction rate (i.e., the ratio of the target assertions/alignments that are corrected with right substitutes) of 70.1 %, 60.9 % and 71.8 %, respectively.

Efficient distributed discovery of bidirectional order dependencies

Bidirectional order dependencies (bODs) capture order relationships between lists of attributes in a relational table. They can express that, for example, sorting books by publication date in ascending order also sorts them by age in descending order. The knowledge about order relationships is useful for many data management tasks, such as query optimization, data cleaning, or consistency checking. Because the bODs of a specific dataset are usually not explicitly given, they need to be discovered. The discovery of all minimal bODs (in set-based canonical form) is a task with exponential complexity in the number of attributes, though, which is why existing bOD discovery algorithms cannot process datasets of practically relevant size in a reasonable time. In this paper, we propose the distributed bOD discovery algorithm DISTOD, whose execution time scales with the available hardware. DISTOD is a scalable, robust, and elastic bOD discovery approach that combines efficient pruning techniques for bOD candidates in set-based canonical form with a novel, reactive, and distributed search strategy. Our evaluation on various datasets shows that DISTOD outperforms both single-threaded and distributed state-of-the-art bOD discovery algorithms by up to orders of magnitude; it can, in particular, process much larger datasets.

Evidence of effect of riparian attributes on listed freshwater fishes and mussels and their aquatic critical habitat: a systematic map protocol

Background Habitat that is necessary for the survival and recovery of a species listed as threatened, endangered or extirpated (i.e., Critical Habitat) is protected in Canada. For freshwater aquatic species, Critical Habitat may include the riparian zone, however, it is unclear how much of this riparian habitat needs to be protected to support the survival and recovery of a listed species. The riparian zone mainly affects aquatic species through its indirect effect on aquatic habitat according to five main processes: erosion, filtration, infiltration, shading, and subsidization. To provide quantitative evidence to support the delineation of riparian Critical Habitat, a systematic map will be used to create a searchable database containing the current state of knowledge regarding the relationships between the riparian zone attributes (e.g., size, vegetation) and fishes and mussels, aquatic features, and riparian processes. Methods We will search for primary research articles in bibliographic databases and relevant organizational websites for primary literature, theses, preprints, and grey literature including reports, along with models using a search string specific to riparian habitat. The results will be screened at title and abstract, and full text levels against predefined inclusion criteria and consistency checking will be performed to ensure the inclusion criteria are consistent across multiple reviewers. Quantitative and qualitative data including study details and methods, the riparian habitat, and the waterbody and upland habitat use will be extracted. The findings of the systematic map will be provided in a manuscript and a searchable database accompanied by a decision tree to support biologists in providing scientifically defensible delineation of riparian Critical Habitat for aquatic species at risk in Canada.

Restoration and Enhancement of Historical Stereo Photos

Restoration of digital visual media acquired from repositories of historical photographic and cinematographic material is of key importance for the preservation, study and transmission of the legacy of past cultures to the coming generations. In this paper, a fully automatic approach to the digital restoration of historical stereo photographs is proposed, referred to as Stacked Median Restoration plus (SMR+). The approach exploits the content redundancy in stereo pairs for detecting and fixing scratches, dust, dirt spots and many other defects in the original images, as well as improving contrast and illumination. This is done by estimating the optical flow between the images, and using it to register one view onto the other both geometrically and photometrically. Restoration is then accomplished in three steps: (1) image fusion according to the stacked median operator, (2) low-resolution detail enhancement by guided supersampling, and (3) iterative visual consistency checking and refinement. Each step implements an original algorithm specifically designed for this work. The restored image is fully consistent with the original content, thus improving over the methods based on image hallucination. Comparative results on three different datasets of historical stereograms show the effectiveness of the proposed approach, and its superiority over single-image denoising and super-resolution methods. Results also show that the performance of the state-of-the-art single-image deep restoration network Bringing Old Photo Back to Life (BOPBtL) can be strongly improved when the input image is pre-processed by SMR+.