Software model-checking as cyclic-proof search

This paper shows that a variety of software model-checking algorithms can be seen as proof-search strategies for a non-standard proof system, known as a cyclic proof system . Our use of the cyclic proof system as a logical foundation of software model checking enables us to compare different algorithms, to reconstruct well-known algorithms from a few simple principles, and to obtain soundness proofs of algorithms for free. Among others, we show the significance of a heuristics based on a notion that we call maximal conservativity ; this explains the cores of important algorithms such as property-directed reachability (PDR) and reveals a surprising connection to an efficient solver of games over infinite graphs that was not regarded as a kind of PDR.

Artificial Intelligence Search Strategies for Autonomous Underwater Vehicles Applied for Submarine Groundwater Discharge Site Investigation

In this study, a set of different search strategies for locating submarine groundwater discharge (SGD) are investigated. This set includes pre-defined path planning (PPP), adapted random walk (RW), particle swarm optimisation (PSO), inertia Levy-flight (ILF), self-organising-migration-algorithm (SOMA), and bumblebee search algorithm (BB). The influences of self-localisation and communication errors and limited travel distance of the autonomous underwater vehicles (AUVs) on the performance of the proposed algorithms are investigated. This study shows that the proposed search strategies could not outperform the classic search heuristic based on full coverage path planning if all AUVs followed the same search strategy. In this study, the influence of self-localisation and communication errors was investigated. The simulations showed that, based on the median error of the search runs, the performance of SOMA was in the same order of magnitude regardless the strength of the localisation error. Furthermore, it was shown that the performance of BB was highly affected by increasing localisation errors. From the simulations, it was revealed that all the algorithms, except for PSO and SOMA, were unaffected by disturbed communications. Here, the best performance was shown by PPP, followed by BB, SOMA, ILF, PSO, and RW. Furthermore, the influence of the limited travel distances of the AUVs on the search performance was evaluated. It was shown that all the algorithms, except for PSO, were affected by the shorter maximum travel distances of the AUVs. The performance of PPP increased with increasing maximum travel distances. However, for maximum travel distances > 1800 m the median error appeared constant. The effect of shorter travel distances on SOMA was smaller than on PPP. For maximum travel distances < 1200 m, SOMA outperformed all other strategies. In addition, it can be observed that only BB showed better performances for shorter travel distances than for longer ones. On the other hand, with different search strategies for each AUV, the search performance of the whole swarm can be improved by incorporating population-based search strategies such as PSO and SOMA within the PPP scheme. The best performance was achieved for the combination of two AUVs following PPP, while the third AUV utilised PSO. The best fitness of this combination was 15.9. This fitness was 26.4% better than the performance of PPP, which was 20.4 on average. In addition, a novel mechanism for dynamically selecting a search strategy for an AUV is proposed. This mechanism is based on fuzzy logic. This dynamic approach is able to perform at least as well as PPP and SOMA for different travel distances of AUVs. However, due to the better adaptation to the current situation, the overall performance, calculated based on the fitness achieved for different maximum travel distances, the proposed dynamic search strategy selection performed 32.8% better than PPP and 34.0% better than SOMA.

MTV-MFO: Multi-Trial Vector-Based Moth-Flame Optimization Algorithm

The moth-flame optimization (MFO) algorithm is an effective nature-inspired algorithm based on the chemical effect of light on moths as an animal with bilateral symmetry. Although it is widely used to solve different optimization problems, its movement strategy affects the convergence and the balance between exploration and exploitation when dealing with complex problems. Since movement strategies significantly affect the performance of algorithms, the use of multi-search strategies can enhance their ability and effectiveness to solve different optimization problems. In this paper, we propose a multi-trial vector-based moth-flame optimization (MTV-MFO) algorithm. In the proposed algorithm, the MFO movement strategy is substituted by the multi-trial vector (MTV) approach to use a combination of different movement strategies, each of which is adjusted to accomplish a particular behavior. The proposed MTV-MFO algorithm uses three different search strategies to enhance the global search ability, maintain the balance between exploration and exploitation, and prevent the original MFO’s premature convergence during the optimization process. Furthermore, the MTV-MFO algorithm uses the knowledge of inferior moths preserved in two archives to prevent premature convergence and avoid local optima. The performance of the MTV-MFO algorithm was evaluated using 29 benchmark problems taken from the CEC 2018 competition on real parameter optimization. The gained results were compared with eight metaheuristic algorithms. The comparison of results shows that the MTV-MFO algorithm is able to provide competitive and superior results to the compared algorithms in terms of accuracy and convergence rate. Moreover, a statistical analysis of the MTV-MFO algorithm and other compared algorithms was conducted, and the effectiveness of our proposed algorithm was also demonstrated experimentally.

OP128 Improving Literature Searching For Evidence On Health Apps: The National Institute For Health And Care Excellence (NICE) MEDLINE And Embase (Ovid) Health Apps Search Filters

IntroductionLiterature searching for evidence on apps in bibliographic databases is challenging because they are often described with inconsistent terminology. Information Specialists from the United Kingdom's National Institute for Health and Care Excellence (NICE) have developed validated search filters for retrieving evidence about apps from MEDLINE and Embase (Ovid) reliably.MethodsMedical informatics journals were hand-searched to create a ‘gold standard’ set of app references. The gold standard set was divided into two sets. The development set provided the search terms for the filters. The filters were validated by calculating their recall against the validation set. Target recall was >90%.A case study was then conducted to compare the number-needed-to-read (NNR) of the filters with previous non-validated MEDLINE and Embase app search strategies used for the ‘MIB214 myCOPD app’ NICE topic. NNR is the number of references screened to find each relevant reference.ResultsThe MEDLINE and Embase filters achieved 98.6 percent and 98.5 percent recall against the validation set, respectively. In the case study they achieved 100 percent recall, reducing NNR from 348 to 147 in MEDLINE and from 456 to 271 in Embase.ConclusionsThe novel NICE health apps search filters retrieve evidence on apps from MEDLINE and Embase effectively and more efficiently than previous non-validated search strategies used at NICE.

Relationships between demographic and behavioural factors and spatial behaviour in missing persons’ cases

To date, limited systematic focus has been directed to examining factors that influence the spatial behaviour of missing people. Accordingly, this study examined whether demographic and behavioural factors were related to distance between missing and found locations in 16,454 archival cases of missing reports from two UK police forces. Findings from ordinal regressions showed that children were more likely to be found at further distances if they were deemed to be at high or medium risk of coming to harm but less likely to be located further away when victims of a violent attack. Adults were more likely to be found at further distances if planning behaviours were present (e.g. had taken their passport), but less likely to if they were above the age of 65 years or suffering from abuse. Findings indicate the role of age, planning and vulnerability on travel when missing. Implications for search strategies and directions for future research are considered.

Spanish contact influence in a Finnish heritage community in Misiones, Argentina

This study examines contact outcomes in Finnish spoken in a heritage community in Misiones province, Argentina, in the 1970s. The data show limited morphosyntactic differences from dialectal varieties of Finnish, and most of the Spanish influence is lexical loans or sporadic codeswitches that have an emphatic function. The results show that beyond established lexical loans, both fluent and less fluent speakers avoid mixing and comment on it when it occurs. Translation and word search strategies show evidence of the speakers’ awareness about language mixing in the interview setting in which data were collected.