Surveillance of dengue vectors using spatio-temporal Bayesian modeling Background: At present, dengue control focuses on reducing the density of the primary vector for the disease, Aedes aegypti, which is the only vulnerable link in the chain of transmission. The use of new approaches for dengue entomological surveillance is extremely important, since present methods are inefficient. With this in mind, the present study seeks to analyze the spatio-temporal dynamics of A. aegypti infestation with oviposition traps, using efficient computational methods. These methods will allow for the implementation of the proposed model and methodology into surveillance and monitoring systems.The study area includes a region in the municipality of Rio de Janeiro, characterized by high population density, precarious domicile construction, and a general lack of infrastructure around it. Two hundred and forty traps were distributed in eight different sentinel areas, in order to continually monitor immature Aedes aegypti and Aedes albopictus mosquitoes. Collections were done weekly between November 2010 and August 2012. The relationship between egg number and climate and environmental variables was considered and evaluated through Bayesian zero-inflated spatio-temporal models. Parametric inference was performed using the Integrated Nested Laplace Approximation (INLA) method. Results: Infestation indexes indicated that ovipositing occurred during the entirety of the study period. The distance between each trap and the nearest boundary of the study area, minimum temperature and accumulated rainfall were all significantly related to the number of eggs present in the traps. Adjusting for the interaction between temperature and rainfall led to a more informative surveillance model, as such thresholds offer empirical information about the favorable climatic conditions for vector reproduction. Data were characterized by moderate time (0.29 -0.43) and spatial (21.23 -34.19 m) dependencies. The models also identified spatial patterns consistent with human population density in all sentinel areas. The results suggest the need for weekly surveillance in the study area, using traps allocated between 18 and 24 m, in order to understand the dengue vector dynamics. Conclusions: Aedes aegypti, due to it short generation time and strong response to climate triggers, tend to show an eruptive dynamics that is difficult to predict and understand through just temporal or spatial models. The proposed methodology allowed for the rapid and efficient implementation of spatio-temporal models that considered zero-inflation and the interaction between climate variables and patterns in oviposition, in such a way that the final model parameters contribute to the identification of priority areas for entomological surveillance. Due to the complexity of estimation involved in spatiotemporal modeling, these dimensions of variation inherent to many epidemiological processes are rarely analyzed together. The present methodology for estimation allows for the rapid and efficient implementation of these models, while considering 1) zero-inflation within SA, 2) interaction among climate variables and 3) different oviposition patterns over the course of the study period. This methodology can contribute to the identification of priority areas for entomological surveillance and targeted fieldwork.. Oviposition activity occurred over the entire course of the study but varied among SAs. The highest ovitrap positivity was 78 % (76-79 %) in SA2, while the lowest one was 38 % (36-38 %) in SA8. The remaining SAs presented ovitrap positivities varying between 55 and 67 % ( Table 2 ). As expected, summertime featured the greatest infestation.. The distance between ovitraps and the border of the campus was assessed based on the hypothesis that A model containing the interaction between temperature and rain was more informative and provides thresholds that could be used to issue alerts. However, the threshold values differed between areas, being significant only in two areas, SA1 and SA3 (Fig. 4) . This variation suggests local microclimate effects not captured by the single meteorological station and can be attributed to the particular characteristics of each area (Table 1) . Minh An and Rocklöv [22] evaluated the effect of the interaction between rain and temperature on the number of dengue cases in Hanoi, Vietnam. They showed rain occurrence and temperatures between 15 and 30°C to correlate to an increase in the number of dengue cases.. Total precipitation accumulated over the two weeks prior to collection contributed to the increase in the number of eggs in five of the SAs, located within both high and low levels of vegetation areas. SA1 and SA3 also featured the effect of rain, but this effect interacted with temperature. Only SA4 showed no association between the number of eggs and rainfall. The relationship between precipitation and the proliferation of A. aegypti is likely to vary on small geographical scales [23] . Rain contributes to the formation of breeding habitats, but this effect will depend on the local availability of containers [24] . During heavy rainfall, these water containers offer favorable conditions for oviposition and the development of immature mosquitoes.. Significant positive relationship between minimum temperature and the number of eggs deposited over the following week was found in almost all SAs. High temperatures increase the rate at which mosquito larvae develop, leading to the rapid subsequent development of adult life forms of the mosquito. Under such conditions, the frequency of mosquito bites in humans also increases [25, 26] . Honório et al. [27] also found a significant positive effect of temperature on A. aegypti egg density in three neighborhoods of the municipality of Rio de Janeiro.. In the present study, we identified spatial patterns consistent with human population in all sentinel areas. Duncombe et al. [28] showed that vector density tends to correlate directly to high population density. A Colombian study also reinforced these findings [29] . The presence or absence of spatial correlation could be influenced by the distance between traps. Our findings suggest that ideal entomological surveillance should occur with weekly visits to traps located between 18 and 24 m apart. This result is important to guide the implementation of ovitrap surveillance systems, but also presents a challenge due to the high sampling effort required. Often surveillance is carried out using more sparsely distributed traps, from 50 m to 200 m apart [7] . One possibility to overcome this problem is to cluster traps in sentinel areas, as done in this study. The joint analysis of the sentinel areas (Hierarchical model) only confirmed the rainfall as driving the number of eggs. Nevertheless, the estimates of spatial and temporal dependence parameters were similar.. The present study had some limitations. Other data, such as wind direction and speed were not available for analysis, as well as other potentially confounding variables, such as the amount and location of breeding sites. Moreover, precipitation data were collected from a weather station 5 km away from the study area. This may introduce bias, as the quantity of rainfall can vary substantially even in close geographical areas.. Aside from these limitations, the results suggest that border distance, minimum temperature and precipitation are all associated with population density of A. aegypti. Maps describing the abundance of eggs identified areas with high potential for transmission, so that control and prevention activities could be developed. The results also indicates the ideal spacing for traps, which constitutes an important aspect of sampling. Summaries of the posterior means of the model's fixed effects and their respective 95 % credibility intervals (CI) are shown in Table 2 . The "interaction" component, whenever shown, represents the effect of the interaction between accumulated rainfall in the two weeks prior to collection and the minimum temperature in the week prior to collection on the number of eggs. In the presence of statistically significant interaction, the primary effects of variables involved in the interaction terms are not interpreted, in order to avoid erroneous conclusions. All the models fit the data reasonably well, with 58 to 88 % of the validation dataset encompassed by the 95 % CI. The validation analysis could capture the oviposition pattern for all SAs, except for the highest number of eggs. Additional file 1 shows the validation analysis per trap for one particular SA (SA6).. The positivity index ranged from 0.38 to 0.78. The area with the least positivity was SA8, and the most "attractive" for oviposition was SA2. Border distance had significant effect on the reduction of the number of eggs in SA2, and contributed to an increase in eggs in SA7. Total accumulated rainfall (Rainfall) was important to explain the increase in the number of eggs in all SAs except SA4. Minimum temperature (Tmin) also significantly contributed to explain the egg frequency in all SAs, except SA8.. Interaction effects between climate variables in SA1 and SA3 suggest that the effect of the quantity of accumulated rainfall (lag 2) on egg abundance changes as a function of the minimum temperature (lag 1). Figure 4 shows how the interaction between these variables influenced egg density, highlighting the change in direction of the effects for values above or below 26.3 mm of rain and 24.6°C minimum temperature in SA1. In this area, an increase in the number of eggs could be expected only if the total rainfall was more than 26.3 mm, and minimum temperatures fell below 24.6°C. In SA3, the effects changed direction according to the thresholds of 14.5 mm and 23.8°C, so that rainfall greater than 14.5 mm and temperatures below 23.8°C favored a reduction in egg density.. The temporal correlation between the weekly average number of eggs was moderate, varying from 0.29 (SA8) to 0.46 (SA2 and SA4). The variance of the nugget effect or measurement error ranged from 0.02 (SA7) to 0.09 (SA5 and SA8). The posterior mean of the spatial effect variance ranged from 1.04 (SA8) to 1.79 (SA4). More variation is explained by the spatial term rather than by the measurement error in all SAs. The empirical range varied from 21.23 to 34.19 m (the maximum distance between traps was 182.6 and 623.8 m) occurring respectively in SA2 and SA8. As these are the distances at which correlation is close to 0.1, we can conclude that the data feature moderate spatial correlation, which slowly decreases with distance.. The mean spatial egg distribution during the study period is presented in Fig. 5 . In each area, the filled circle indicates the traps' location. In general, the highest concentration of eggs was found in areas that bordered settlements with high population densities (slums), and in those close to campus buildings, where pedestrian foot traffic was heavier. Within each area, egg distribution was heterogeneous. Additional file 2 shows weekly changes in the number of eggs in SA1 throughout the study period using an animated map.. The hierarchical model estimated an average positivity of 62.2 %. Border distance was not important to explain the variations in the number of eggs, so it did not enter in the final model. The accumulated rainfall in the two weeks prior to trap installation was statistically significant but the minimum temperature in the previous week was not, as well as the interaction between them. As expected, higher rain rates (β 2 = 0.08 [95 % CI: 0.01 − 0.16]) was associated with larger quantities of eggs. The variability attributed to the spatial-structured effect (σ 2 ω = 8.98 [95 % CI: 6.98 − 12.42]) was greater than that attributed to measurement error (σ The complexity of dengue transmission has motivated the development of many studies to assess the numerous factors related to the circulation and persistence of this disease in human populations. While significant progress has been made, numerous questions remain unanswered, and an effective dengue control plan is still an open problem. No effective vaccines or antiviral drugs are currently available, impeding a direct intervention on the human link in the dengue transmission cycle. As such, current control measures are still focused on reducing the vectorial capacity of Aedes aegypti.. The Household Infestation index (HI) and the Breteau index (BI) are the standard mosquito abundance measurements used to evaluate the effectiveness of vector control strategies [1] . However, these indices, based on the survey of breeding sites with mosquito larvae, are poorly correlated with the abundance of the adult mosquito population, which is directly responsible for the disease transmission [2] . For example, a study has shown high dengue incidence when HI was below 3 % in Salvador city, Northeastern Brazil [3] .. Ovitrap has been proposed as an alternative tool for Aedes aegypti monitoring in areas with low mosquito abundance [4] . This trap was created by Fay and Eliason [5] and perfected by Reiter and Gubler [6] , and provides measures of ovipositing activity. Although not a direct measure of mosquito abundance, studies have shown a strong correlation between egg count and the density of the female mosquito population [7] .. Despite the advantages of trapping over larval surveys, this approach is still scarcely applied to surveillance. One of the main reasons for this is the fact that the sampling and statistical properties of the measurements produced are not entirely understood yet. In this study, data from a long-term surveillance program carried out under very controlled conditions in eight sentinel areas, provide an opportunity to develop and test innovative models and contribute to the development of an analytical framework to be implemented in Aedes aegypti monitoring systems. The models proposed are computationally intensive and more efficient methods that allow for their implementation in surveillance and monitoring systems were investigated. Such information contributes to the development of Aedes control activities focused on areas and time periods affected by the most severe mosquito infestations.

O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Comparative study on gene set and pathway topology-based enrichment methods Background: Enrichment analysis is a popular approach to identify pathways or sets of genes which are significantly enriched in the context of differentially expressed genes. The traditional gene set enrichment approach considers a pathway as a simple gene list disregarding any knowledge of gene or protein interactions. In contrast, the new group of so called pathway topology-based methods integrates the topological structure of a pathway into the analysis.We comparatively investigated gene set and pathway topology-based enrichment approaches, considering three gene set and four topological methods. These methods were compared in two extensive simulation studies and on a benchmark of 36 real datasets, providing the same pathway input data for all methods.Results: In the benchmark data analysis both types of methods showed a comparable ability to detect enriched pathways. The first simulation study was conducted with KEGG pathways, which showed considerable gene overlaps between each other. In this study with original KEGG pathways, none of the topology-based methods outperformed the gene set approach. Therefore, a second simulation study was performed on non-overlapping pathways created by unique gene IDs. Here, methods accounting for pathway topology reached higher accuracy than the gene set methods, however their sensitivity was lower.We conducted one of the first comprehensive comparative works on evaluating gene set against pathway topology-based enrichment methods. The topological methods showed better performance in the simulation scenarios with non-overlapping pathways, however, they were not conclusively better in the other scenarios. This suggests that simple gene set approach might be sufficient to detect an enriched pathway under realistic circumstances. Nevertheless, more extensive studies and further benchmark data are needed to systematically evaluate these methods and to assess what gain and cost pathway topology information introduces into enrichment analysis. Both types of methods for enrichment analysis require further improvements in order to deal with the problem of pathway overlaps. Enrichment analysis is a useful and popular approach to ease interpretation of high throughput data. We comparatively investigated 3 gene set (GS) and 4 pathway topology-based (PT-based) methods in extensive simulation studies and on real benchmark data.. Our results are consistent with some already published findings: As expected, the self-contained method behaved differently than the competitive ones. The ranking methods were more sensitive than over-representation analysis methods when expression changes were moderate. Further, we demonstrated that on original KEGG pathways none of the PT-based methods was clearly outperforming the GS approach, neither in simulations nor in benchmark testing. This changed in the simulation study with non-overlapping pathways, where the PT-based approach exceeded simple GS tests. This suggests that further conceptual work has to be done to deal with the problem of pathway overlaps.. From the gene set methods Wilcoxon rank sum test performed comparably as topological methods in most settings, and it is much easier to use and re-implement with different input data than PT-based approaches.. Including topology to test for enrichment of a pathway is an interesting approach. It introduces additional information into the analysis and allows attractive visualizations of the pathway graphs. However, it needs to be further explored whether the additional biological insights justify the increased complexity of the PT-based enrichment analyses. In order to place long lists of differential genes into a context of biological processes and pathways the enrichment analysis strategy is widely used. In this work we compared standard gene set (GS) enrichment tests with methods, which attempt to incorporate pathway topology information into analysis.. Comparing GS methods and pathways topology-based (PT-based) enrichment approaches is challenging in two regards. First, the pathway input data have to be corresponding for all methods to ensure a fair comparison. Therefore, we parsed a BioPAX export of the KEGG database and transformed the pathways into gene sets as well as various interaction graph representations for the different methods. Second, it is difficult to simulate expression data for PT-based methods. The signal in a pathway is mediated via multiple biological mechanisms. Capturing a pathway deregulation in a graph and reflecting this alteration in the synthetic expression data is an intriguing task. To our knowledge there is no coherent work published on this topic. We made one of the first attempts to generate expression data mirroring the topology of the deregulated pathways. However, there are several limitations in our simulation scheme. For instance, multivariate approaches usually require more complex covariance matrices for a fair and unbiased evaluation, therefore, we have not included multivariate self-contained methods.. We decided to use 3 approaches to allocate affected genes to a pathway: gene community, betweenness and neighbourhood. However, in a certain setting some methods might be favoured due to their inherent algorithms, e.g. both CePa methods by betweenness and PathNet by neighbourhood designs. Further, it could be questioned how well these network measures reflect the real perturbation signals in a pathway.. In the first simulation study we could not identify any PT-based method as outstanding neither for any parameter configuration, nor for the overall accuracy measure. The pathway input for this study was represented by original KEGG pathways, which exhibit considerable gene overlap among each other. When a pathway was called deregulated it received a certain number of genes assigned as affected according to the detection call level. However, a single gene was on average present in 2.4 pathways. This resulted in a number of pathways, which were not considered as deregulated but also contained affected genes.. These pathways then showed up as false positives and consequently led to a very low specificity and accuracy of all methods in study 1. However, one could assume that these 'accidental' affected genes were allocated randomly in the non-deregulated pathways, whereas in the deregulated pathway they were placed in a topological context. Therefore, it could be expected that the PT-based methods would overcome the problem of these false positives, however, this seems not to be the case.. It was already demonstrated that ranking methods are able to detect modest signals of deregulation better than the ORA approach [20] . We further showed that GS ranking methods were more sensitive than any of the PT-based methods when gene expression changes were Fig. 6 Overall sensitivity, specificity and accuracy in the simulations. Distribution of 3 measures for each method over 17000 simulation runs for study 1 with the original pathways with overlapping genes and study 2 with non-overlapping pathways with unique gene IDs weak (mean = +/− 1). The CePa GSA method exhibited a clearly different behaviour than the others, which was expected from the single self-contained method included in this work. Prominently different performance of this self-contained method could be further enhance by the fact that CePa computes for each pathway five p-values corresponding to different centrality measures and the authors of the method recommend to use the lowest value. Therefore, its overall sensitivity in the first study was higher than all the other competitive methods [12] . On the other hand, its specificity was utterly lost when a lot of pathways were deregulated (study 1, N = 70). Similarly, in the diseased benchmark datasets CePa GSA was the best in identifying target pathways but it also identified more than half of all KEGG pathways as significant. Depending on a disease, multiple pathways could be altered. However, it could be questioned whether such a number of pathways is realistic or it reflects lack of specificity of this method.. In the second simulation study with non-overlapping pathways the overall specificity markedly increased, mainly for the PT-based methods. This was also reflected in the best accuracy for these four PT-based methods.. Interestingly, the overall specificity of KS was the lowest among all methods and it was also always decreasing when more genes were affected (see Additional file 4, DC = 70 %, N = 70, size = big). That could stem from its null hypothesis, as it actually tests whether a gene set or its complement is significant [32] . In a setting when it was the complement it resulted in the false positive pathways in our simulations.. Because of the limitations of the simulations, which can never completely capture complex biology, we compared methods also on the real expression data. It is not possible to judge overall accuracy on these 36 benchmark datasets but PathNet and WRS showed reasonable ability to identify the target pathways. This suggests that simple GS approach might be sufficient for detecting enriched pathways. Analysis of gene expression experiments typically yields long lists of differentially expressed genes (DEGs) [1] . To ease interpretation of such results it has been proposed to analyse expression data in the context of biological pathways or other biologically meaningful gene sets instead of individual genes [2] . There are many tests, which aim to detect pathways significantly enriched between two experimental conditions [3] [4] [5] [6] . These tests were implemented into a plethora of methods that differ in many aspects ranging from null hypothesis formulation, through statistical framework up to pathway data encoding, database support and software availability.. We were interested to evaluate different methods for analysing gene expression data in the context of signalling pathways, with a special focus on comparing methods with different pathway representation strategies. There are different approaches how to handle a pathway in enrichment analysis. The traditional approach considers a pathway as a simple gene list omitting any knowledge of the gene and protein interactions. Methods belonging to this category are commonly called gene set (GS) analysis methods. Another way of integrating a pathway into enrichment analysis takes into account its graphical structure and/or topological measures. One of the first pathway topology-based (PT-based) methods was impact analysis proposed by Draghici et al. [7] . Since then this has approach become very popular, resulting in a number of PTbased algorithms being published [8] [9] [10] [11] .. Enrichment methods can be divided into two groups based on the null hypothesis: (i) competitive methods which are naturally linked with gene sampling for p-value calculation and (ii) the group of self-contained methods which is associated with subject sampling [12] . The basic difference between these two groups is that competitive methods compare genes in a pathway to its complement usually represented by the rest of the genes measured in the experiment, while self-contained methods consider only genes within a pathway and test their association with the phenotype. Both approaches have their limitations. On the one hand, competitive methods coupled with a gene sampling model for p-value calculation assume independence of genes, which is known not to be true. On the other hand, self-contained methods were criticized for being too powerful and thus yielding too many significant gene sets. Also the number of replicates in the experiments is often too low for subject sampling [12] .. Another classification of enrichment methods separates them into over-representation analysis (ORA) and functional class scoring (FCS) approaches [13] . ORA is commonly referring to 2×2 table methods such as Fisher's exact test, hypergeometric test and chi-squared test. It represents exclusively the competitive approach. The ORA methods require a strict cut-off in the list of DEGs and therefore the results are strongly dependent on the chosen threshold. FCS comprises methods, which first score genes and then transform gene level scores into pathway level scores. This group includes both competitive and self-contained methods, depending on the pathway-level transformation and significance assessment of pathway level score. Most of the PT-based methods can be classified into either ORA or FCS, however in some cases it might be difficult to draw a strict line.. From the user's point of view there are several features of the enrichment methods to be considered besides classification of the methods according to methodological and statistical framework. For instance, the implementation and availability of the software can determine how popular a method becomes. Furthermore, several pathway databases such as Kyoto Encyclopedia of Genes and Genomes (KEGG) [14] , Reactome [15] , Pathway Interaction Database [16] or BioCarta [17] make data available for pathway analysis. While it is rather straightforward to supply simple gene set of a pathway for GS methods, providing a pathway with topology information and integrate it into a PT-based method can be more difficult. Therefore, the utility of PT-based methods also depends on their support of different pathway databases.. Several studies comparing different GS analysis methods were already published [18] [19] [20] , as well as review papers offering surveys of PT-based methods [13, 21] . However, to our best knowledge there is no paper comparing the GS against the PT-based approach systematically.. Therefore, the aim of our study is to evaluate GS versus PT-based approaches using simulated gene expression data as well as benchmark datasets. For comparability of the methods we focused mainly on competitive ones, including three GS tests and four PT-based methods implemented in the R statistical computing environment (see Table 1 ). These seven methods represent both ORA and FCS approaches.. To perform a fair comparison of the different methods we faced two major challenges: First, it was necessary to provide the same pathway data inputs for all methods, which was in particular challenging for PT-based methods. The integration of topological pathway data is described in detail in the third section of the Methods. Second, to simulate expression data for evaluation of PT-based methods was a comprehensive problem, which resulted in a complex simulations scheme. Hence, we described Simulations as a separate chapter. In this chapter we present in detail 3 GS and 4 PT-based enrichment methods and their use within this work. Methods were classified according to the representation of a pathway into the gene set (GS) enrichment and the pathway topology-based (PT-based) methods. Second column stratifies the methods into over-representation analysis (ORA) and functional class scoring (FCS). However, for PT-based methods this classification is not always explicit, therefore we used '-like' suffix and 'unclass.' for an unclassified method. Third column shows the utilized R-functions for GS methods and versions of R-packages of PT-based methods. Next column summarizes the pathways databases which are provided within the R-packages. According to the null hypothesis most of the methods are competitive, only the GSA variant of the CePa method is self-contained Further, we describe how pathway data were processed and integrated into the methods. The last section of the Methods introduces the analysis of benchmark data.

O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O B O O O O O O O B O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Natural Language based On-demand Service Composition The widespread of Web services in the ubiquitous computing era and the impossibility to predict a priori all possible user needs generates the necessity for on-demand service composition. Natural language is one of the the easiest ways for a user to express what he expects regarding a service. Two main problems need to be solved in order to create a composite service to satisfy the user: a)retrieval of relevant services and b) orchestration/composition of the selected services in order to fulfill the user request. We solve the first problem by using semantic concepts associated with the services and we define a conceptual distance to measure the similarity between the user request and a service configuration. Retrieved services are composed, based on aspect oriented templates called Aspects of Assembly. We have tested our application in an environment for pervasive computing called Ubiquarium, where our system composes a service according to the user request described by a sentence. The implementation is based on the WComp middleware that enables us to use regular Web services but also Web services for devices. Background. Since Web 2.0 marked it's appearance as a concept in the fall of 2004 and introduced the principle of the Internet as a platform [19] , the complexity and diversity of this platform grew together with the more enhanced features it was providing to its users. Given the fact that the software in the Internet era is delivered as a service, not as a product and there is no release cycle for the services, it is the user who's in charge of finding a service and using it.. In a near future services will be more diverse and widespread as computers will become ubiquitous. In the same way the information across the Web is structured, classified and then presented to a user that sends a natural language request to a search engine, so a collection of applications should be assembled, classified and deployed using the services that are found within a given context based on a similar unrestricted language request coming from the user.. The problem. In a context where various services with different functionality are available, it's possible to compose new services on-demand, based on a user request, only when the right selection of components is used.. On-demand service composition involves two operations: service retrieval and service orchestration. Service retrieval refers to identifying those specific services that are addressed by the user request or the closest functional match to the request. The transition from a natural language request to a list of services is a challenge that is even more difficult when no restrictions are added to control the request. Service orchestration or service assembly is the process of linking the retrieved services in a functional flow so that the user demand is fulfilled. Both mentioned problems make the object of this paper, but while service retrieval was the field of our research, for service orchestration we used an existing approach.. Scenario. We consider the following scenario to illustrate the purpose of dynamic service composition based on natural language requests. A handicapped person lives inside an intelligent house, surrounded by intelligent devices, sensors and actuators. Each device has its own inputs and outputs and is able to process different types of data, leading to a large number of possible functional combinations of those devices. The person in the intelligent house wants to use those devices by combining their functionality (e.g. link the output from a sensor to the input of an actuator), but his disability prevents him to physically interact with the devices or he simply lacks any technical knowledge. Therefore, he expresses his need using the natural language (either written or spoken): "I want to use my remote control on the wheel chair to turn off the light, change the channel on TV and play some music on the media center". Each device the user addresses through his request (remote control, light, TV, media center) provides a different service with specific actions that can be used in various configurations. Finding a way to sort these configurations by relevance to the user's request is a key requirement for the imagined scenario. Also, when one of the devices the user wants to use is not present in the intelligent house or it was replaced with an updated version, the system should adapt and assemble a service that is the closest match to the user's need.. Approach. Dynamic service composition solves the problem of adaptation to different contexts and user preferences. Also, by composing services on demand, the learning curve required for the user to work with new configurations is reduced as the user "gets what he wants" from the application. Existing systems for dynamic service composition based on natural language requests either provide a restricted natural language interface or don't offer support for adaptation to structural and behavioral changes of the service configuration.. We start with an initial set of services that are discoverable across a network. The user requests a completely new service using an unrestricted natural language sentence. In order to find specific devices to satisfy the request, we use semantic concepts and define a conceptual distance between the request and a service configuration. Concepts are leafs on a lexical tree that is generated by deriving and generalizing a notion. Once the services that match the request are identified, some aspect oriented advices are used to connect the services so that when a service disappears from the context or a new service is made available, the service configuration adapts.. Outline. This paper is organized as follows: the next section examines the problems a dynamic service composition system should solve in order to be usable in the modern context of Web services. Section 3 describes the solution we propose including the principles that lead to this solution, while section 4 focuses on the design and implementation patterns we used, along with the test results. Section 5 examines some of the existing dynamic service composition approaches. The paper ends with conclusions and further research. This paper proposes a new method for assembling services on demand, starting from the user request expressed in natural language. We use a semantic analysis of the user request, in order to identify the services described by concepts that are related to concepts from the user request. Retrieved services are then composed, based on composition patterns, called AoA (Aspects of Assembly). The uses of patterns, which assure that the new service is always valid, compensate the ambiguity of the natural language.. Another important advantage of the AoA patterns, comparing to other existent pattern-based approaches, is the fact these patterns may be superposed by composition. Thus, a large number of combinations are possible using a given set of patterns. Additionally, for a given set of services, the AoA mechanism applies only the patterns that lead to valid services.. The solution was implemented on the WComp platform and tested in a dedicated ambient computing environment, called Ubiquarium, using real and virtual intelligent devices/services.. The service composition is user driven, by natural language (voice) and allows the user to get the service on-demand. From this point of view, our solution is less restrictive than the other solutions described in the state of the art section.. An important advantage of our solution is the reuse of WordNet free dictionary, which is acting like ontology. Due to this, we can relax very much the limitations for the natural language, imposed by solutions where an ontology (usually restricted) must be created by the developer. Otherwise, the creation of a rich ontology is a very costly task and our solution succeeded to avoid it by reusing WordNet. This choice has another important advantage: it solves the problem of dealing with different ontologies and does not need to impose a common ontology (the only requirement is to use English).. A particular aspect of our proposal is the mixed approach: semantic and pattern-based. This approach combines the advantages of the both: thanks to composition patterns, it allows us to build complex composite services, which are always valid and functional. With other approaches (interface, logic, semantic based), that are not using patterns/templates, it is very difficult to create complex architectures that are valid and work correctly.. As future work, we intend to extend our solution for dynamic service adaptation (at runtime) and this should be feasible because WComp was designed for dynamic service reconfiguration in Composing Web services on the basis of natural language requests. The solution described in [4] and [5] assumes that the user requests are expressed with a controlled subset (a narrow vocabulary) of natural language. The sentence that represents the userŐs request is transformed into a flow model using templates (e.g. if . . . then . . . else, when . . . do). Verbs are used to identify the action and its parameters. Each available service is paired with a well-defined set of keywords. OWL-S annotations are used to provide operation semantics and an ontological classification of Web services. The operations act as nodes of a direct acyclic graph and the relations among their IOPEs (Inputs, Outputs, Preconditions and Effects) establish arcs. The graph is translated into an executable service at invocation time.. The example the authors use to sustain the proposed solution uses the phrase "If there is any cinema showing "Big Fish" in Turin then send a SMS to Dario containing "Lets go to the movies tonight!"" An if . . . then template is used to identify the flow model. In the next step, called context focus, the service types are identified: cinema, SMS. The verb (send) triggers the parameter retrieval stage where IOTypes recognizers based on format (Date, Time, Telephone NumbersÉ) and values (City namesÉ) are used to extract the actionŐs parameters.. This solution establishes a synergy between the semantic service descriptions and the Natural Language interpretation of user requests, through a common ontology and a consistent lexical vocabulary. Therefore it canŐt be used in active environments where new components that act as black-boxes appear and disappear from the context dynamically. Also, the use of a controlled subset of natural language makes it non intuitive for the user as he is restricted to the use of templates when expressing a request.. Semantics-based dynamic service composition. Papers [12] and [13] propose the CoSMoS model and the SegSeC platform for dynamic service composition. Their idea is to transform the semantics of the user request into a semantic graph. Nodes in the semantic graph represent operations, inputs, outputs and properties of a component, as well as their data types and concepts. Arcs (labeled links) represent the relationships among the nodes. Concepts, entities representing abstract ideas actions are used to annotate the semantics of the operations, inputs, outputs and properties of components. The user request is parsed and the components addressed by the user form a workflow.. The example in [13] uses the phrase "Print directions from home to restaurant". The semantic graph contains the predicate (print), the target of the action (direction) and the parameters (home, restaurant). The workflow, containing the retrieved components, is executed as soon as it satisfies the user request. This analysis takes place in a step called semantic matching and consists in a test that verifies that all the links that appear in the user request also appear in the graph that models the workflow.. The authors of [13] admit that their solution is not suited for environments where a large number of components are deployed. The platform lacks the feature of providing a solution in the case where the workflow doesnŐt satisfy the userŐs request. If the generated workflow doesnŐt match exactly the user request, then the dynamic service composition fails. Also, the ability of the implementation to discover certain components is to be questioned because itŐs limited to work with a narrow set of keywords and it lacks a vocabulary.. Web service with associated lexical tree. The invention claimed by Alcatel [16] relates to a method to mark-up a Web service in order to allow finding and retrieving said service via a natural language request. A lexical tree, built by deriving the service description, finding synonyms and related forms of the derived keywords, is associated to each service. Finding a service based on the user request resumes to comparing the natural language query to the lexical tree of each Web service. This method of retrieving a Web service proves to be the most appropriate when dealing with natural language requests. The invention however doesnŐt exploit the full potential of this finding, as it lacks service composition.

B I O B B I O O O O O O O O O O O O O O O O O O O O O O O O O B B I B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O B I O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O B I O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O B O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O B I


An autonomous vehicle sequencing problem at intersections: A genetic algorithm approach This paper addresses a vehicle sequencing problem for adjacent intersections under the framework of Autonomous Intersection Management (AIM). In the context of AIM, autonomous vehicles are considered to be independent individuals and the traffic control aims at deciding on an efficient vehicle passing sequence. Since there are considerable vehicle passing combinations, how to find an efficient vehicle passing sequence in a short time becomes a big challenge, especially for more than one intersection. In this paper, we present a technique for combining certain vehicles into some basic groups with reference to some properties discussed in our earlier works. A genetic algorithm based on these basic groups is designed to find an optimal or a near-optimal vehicle passing sequence for each intersection. Computational experiments verify that the proposed genetic algorithms can response quickly for several intersections. Simulations with continuous vehicles are carried out with application of the proposed algorithm or existing traffic control methods. The results show that the traffic condition can be significantly improved by our algorithm. Transportation has always been a crucial aspect of human civilization, but it is only since the second half of the 20th century that the phenomenon of traffic congestion has become predominant due to the rapid increase in the number of vehicles and in the transportation demand (Hall and Papageorgiou, 1999) . Especially over the last decade, traffic congestion attracted extensive attention because of the worldwide energy crisis and environmental concerns.. The conventional method of preventing or reducing congestions in modern cities is based on the traffic signal at intersections. The traffic signal assigns the right-of-way to a stream of vehicles and pedestrians in order to guarantee their safe crossings. The specification of the signal setting (traffic control strategy) has a major impact on intersection capacity and efficiency. Traffic control strategies at intersections generally fall into two basic categories: pre-timed control, which is also called fixed-time control, and semi/fully traffic actuated control. The first category uses the historical data of traffic demand to calculate the signal setting, e.g., the TRANSYT (traffic network study tool) system (Robertson, 1969) . The second strategy, the traffic actuated control, which is also known as the traffic-responsive strategy, has been attracting more and more attention since the 1980s. This control strategy makes use of real-time measurement like the traffic flow rate, which is detected by loop detectors, to specify the signal setting in real time. The most notable system of this kind is SCOOT (Split Cycle Offset Optimization Technique) (Hunt, 1982) . However, both control strategies are based on the estimation of traffic flow rates.. Since the flow rate is a continuous variable that needs a period of time to be estimated, there are always big deviations between the last computed value and the actual one. Besides, the traffic signal is assigned to a stream of vehicles for a period of time. The traffic control command cannot adapt to the fluctuation of the traffic state quickly. Hence, traffic control at intersections based on traffic signals limits the potential of improving intersection capacity.. Since the early 1990s, the development in information systems has provided us with an opportunity to overcome these drawbacks.. The technology of wireless communication like WiFi, WiMax and 3G enabled Vehicle to Vehicle (V2V) communication and Vehicle Infrastructure Integration (VII), which enforce the link between vehicles, infrastructure and the driving environment (Kato et al., 2002; Gradinescu et al., 2007; Chisalita and Shahmehri, 2002) . Besides, advances in the fields of computation and sensor technologies lead to the emergence of fully autonomous vehicles, which take complete control of vehicle operations and eliminate the driver from the control loop, at least in a specific area (Dresner and Stone, 2004; . Various applications of autonomous vehicles have been demonstrated in Europe (Bertolazzi et al., 2010) , Japan (Aotani et al., 2002) and the United States (Shladover et al., 1991; Shladover, 2007) . Under this background, the concept of Autonomous Intersection Management (AIM) has attracted great interests over the last decade.. In the framework of AIM, autonomous vehicles communicate with each other or with roadside infrastructures to exchange the information of their states for ensuring driver safety and improving travel efficiency. More specifically, based on the VII technology, the roadside infrastructure at intersections, which can be seen as a controller, can communicate with approaching vehicles continuously. Vital vehicle data such as vehicle speed, position and destination are collected by advanced sensors and sent to the controller in real time. Hence, it is possible to elaborate a traffic control strategy with considering vehicles to be independent individuals. In other words, the right-of-way is assigned to each vehicle according to its state and the state of the whole intersection.. Only vehicles that have received the right-of-way can get through the intersection. Traffic control aims at determining the vehicle passing sequence, which is a sequence of distributing the right-of-way.. However, to implement this new control method, we mainly face two difficulties:. • First, how to exchange the information among vehicles or between vehicles and roadside infrastructure.. • Second, less studied, how to find an efficient vehicle passing sequence to maximize the traffic throughput at intersections while maintaining driver safety.. For the first difficulty, research on wireless protocols and advanced devices used in autonomous vehicles has been well studied (see, e.g., Dresner and Stone, 2004; Huang and Miller, 2003; Nadeem et al., 2004) . The second one deserves more attention. Most research determines the vehicle passing sequence based on a simple control policy "First In First Out" (FIFO) (Dresner and Stone, 2004; Lachner, 1997) . Although this policy requires very low computational cost, it limits the potential of maximizing the capacity of intersection. Recently, researchers have been paying more attention to optimize vehicle passing sequences. Li and Wang (2006) enumerated all feasible vehicle passing sequences and used trajectory planning algorithms to find the most efficient one. However, they admitted that the algorithms were not efficient enough because the complexity increases exponentially with the number of vehicles and lanes. Wu et al. (2009) presented a dynamic programming algorithm to get an optimal solution based on AIM, but they only considered a simple isolated intersection with two lanes. Indeed, an intersection consists of a number of approaches and each approach may have one or more lanes, which will render considerable combinations of the passing sequence. Thus, how to reach a satisfactory passing sequence at a relative low computational cost becomes a big challenge. Besides, another common concern about the strategy based on VII is that it increases the cost of building and maintaining infrastructures at each isolated intersection (Li and Wang, 2006) . In fact, since congestion in modern cities is usually caused by several adjacent intersections located in dense street networks, it is natural to extend the control strategy to several adjacent intersections with only one controller, but this change will increase the computational cost.. To solve these difficulties, in our earlier works (Yan et al., 2009; we presented some useful structural properties of the proposed new control strategy at an isolated intersection. A branch-and-bound algorithm was designed to find an optimal passing sequence for all detected vehicles for the isolated intersection. However, if we extend the control strategy to several adjacent intersections with only one controller, an exact algorithm like branch and bound cannot be fast enough for all intersections in the sense of computational times. Thus, in this paper we propose a genetic algorithm to solve the sequencing problem efficiently. We also present a technique for combining certain vehicles into some basic groups taking into consideration the proposed properties. This will help us to reduce the search space.. The rest of this paper is arranged as follows. In Section 2, detailed assumptions of the studied problem are described, along with some basic notions of traffic control at intersections. Section 3 presents the technique for partitioning certain vehicles to fundamental mini-groups. A genetic algorithm is presented in Section 4 to solve the problem efficiently. A dynamic programming algorithm is also devised to evaluate the solution quality of the genetic algorithm. In Section 5, computational experiments show that the proposed genetic algorithm can decide on a vehicle passing sequence in less than 0.5 seconds for 100. An autonomous vehicle sequencing problem at intersections: A genetic algorithm approach vehicles with small deviations from optimal solutions. Simulations with a continuous traffic flow are carried out at four adjacent intersections. The results indicate that the proposed algorithm can efficiently improve the traffic condition. Conclusions are drawn in Section 6. In this paper, we studied the autonomous vehicle sequencing problem at adjacent intersections under the framework of AIM. The VII technology was used to obtain each vehicle's information.. The several intersections considered were decentralized to several isolated intersections and at each isolated intersection; vehicles were treated as discrete individuals.. Our objective was to minimize the overall evacuation time at each decision.. In order to obtain an optimal or a near-optimal vehicle passing sequence, a fundamental mini-group algorithm based on the properties our earlier work was devised to combine certain vehicles of the same compatible stream group together as the minimum unit. Then we designed a genetic algorithm which adopts the binary encoding scheme or permutation encoding scheme to decide on the vehicle passing sequence each time. A heuristic SET was also proposed to decode the chromosome obtained by the binary encoding scheme. It can also be used independently to find a vehicle passing sequence. A dynamic programming algorithm was also presented for finding an optimal solution.. Two encoding schemes of the GA, the heuristic SET, dynamic programming and the branch and bound algorithm in our earlier work, were compared in computational experiments. The results showed that the proposed genetic algorithm can decide on a vehicle passing sequence in less than 0.5 seconds for 100 vehicles with small deviations from optimal solutions. Simulations with a continuous traffic flow at a four-intersection network were also implemented. The results indicated that the proposed algorithm can efficiently improve the traffic condition.. In future work, differences between normal vehicles and special used vehicles such as ambulances or police cars will be considered. Special use vehicles should have the privileges to pass through intersection. Each vehicle will have a weight of priority and we need to make vehicles with high weights pass the intersection as quickly as possible while satisfying certain objectives. More constraints and rules will be considered in the next stage of our work to make the control strategy more suitable for real applications.

O O O O O O O O B I O O O O O O O O O O O O O O O B I I O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O B I O O O O O O O O O O O B I O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Achieving Process modeling and Execution through the Combination of Aspect and Model-Driven Engineering Approaches Abstract. One major advantage of executable software process models is that once defined, they can be simulated, checked and validated in short incremental and iterative cycles. This also makes them a powerful asset for important process improvement decisions such as resource allocation, deadlock identification and process management. In this paper, we propose a framework that combines Aspect and Model-Driven Engineering approaches in order to ensure process modeling, simulation and execution. This framework is based upon UML4SPM, a UML2.0-based language for Software Process Modeling and Kermeta, an executable metaprogramming language. Complementary to the use of traditional Verification and Validation (V&V) based approaches, it has been widely recognized that the quality of the software development process also has a direct impact on the quality of the software. By capturing team's best practices, task ordering, flows of artifacts, agent coordination and communications, process models become nowadays an important asset to ensure repeatability and quality in building software.. Recently, driven by the pressure for more accurate results and shorter time-to-market, a demand for executable process models emerged. Executable process models are process models that can be used not only for documenting processes and methods but also for the support of their execution. Indeed, executable process models can be used to coordinate between agents, to enforce artefacts routing between process's steps, to ensure rules and constraints integrity and process deadlines. They can also be of an effective aid since they can be used for simulation and testing. Simulation results can be used as a basis for important improvement decisions such as resource allocation, deadlock identification, estimation of the project duration and many other aspects that have a direct impact on the process and thus on the quality of the delivered software.. During the last two decades, the need for executable Software Process Modeling Languages (SPML) has been widely recognized.. Osterweil opened the way with his seminal work "Software Processes are Software Too" (Osterweil 1987) . He introduced the notion of Process Programming, which consisted in representing software processes in terms of computer-readable programs. The main goal behind this was to ensure agent coordination and the automation of process's repetitive and non-interactive tasks through the execution of process programs. The process programming trend stimulated many research works and had as an impact, the emergence of a multitude of SPMLs. These SPMLs were based on some well-known programming languages (e.g., Ada, LISP) or formal formalisms such as Petri Nets and put a strong emphasis on the executability aspect.. One of the lessons learned from these first-generation languages is that comprehensibility and communication of process's agents around process models is at least as important as their degree of formality (Fuggetta 2000) . The use of low-level formalisms by some process description languages, the lack of flexibility and the impossibility for non-programmers to use them, were among the main causes of their limited adoption.. Another fact that became manifest to the software process modeling community was the critical need of having a standard formalism for representing and exchanging software processes. Instead of reinventing the wheel, many industrial and research teams were attracted by the success of UML (Unified Modeling Language) and explored the possibility of using it as a process modeling language (Chou and Chen 2000) (Di Nitto et al. 2002) (OMG SPEM1.0 2002) (Franch and Rib 1998) . UML is standard, provides a rich set of notations and diagrams, extension mechanisms and whatever its advantages and drawbacks, it is undeniably one of the most adopted modeling languages of this decade. Experiences with UML were not restricted to the software process community but covered other areas such as the business process and the workflow domains (OMG WFMS 2000) . However, these experiences faced in their turn a major barrier. Despite the expressiveness of the language, UML models are not executable. Process models were used as contemplative rather than productive assets. An example of such propositions in the industry is the OMG's SPEM standard (Software Process Engineering Metamodel) (OMG SPEM1.0 2002) . While execution was out of the scope of the first version of SPEM (i.e. SPEM1.1), it has been established as a mandatory requirement in its second revision (i.e. SPEM2.0). Unfortunately, the recently adopted standard still fails in ensuring this requirement.. In this paper we propose to deal with the executability issue in the context of UML-based process modeling languages. At this aim, we propose a framework and an approach for modeling and executing software processes. This framework is based on our dedicated language for software process modeling called UML4SPM (UML-based Language for Software Process Modeling) (Bendraou et al. 2005 ) and an execution support. UML4SPM comes in form of a MOF (Meta Object Facility)-compliant metamodel (OMG MOF 2006) , a notation and semantics that extend the UML2.0 standard. For the execution support of UML4SPM, the semantics of the metamodel is defined in terms of operations and instructions in order to form what we call the Execution Model. The Execution Model is then used as a basis for the realisation of the execution support. In this paper we have experienced two approaches for implementing the Execution Model. The first one consists of a Java implementation using the Visitor design pattern. The second one is based on a metaprogramming language called Kermeta (Muller et al. 2005 ) and the use of aspect oriented modeling techniques. We will discuss both process execution approaches, give advantages and inconvenient of each one and finally discuss the suitability of UML in general for the definition of executable process models. In a previous work (Bendraou et al. 2007) , not presented here, we also explored the possibility of transforming UML4SPM process models into BPEL (Business Process Execution Language) (OASIS BPEL 2007) in order to execute them and we highlighted the limitations of such approach.. It is worth noting that the approach described in this paper for building an executable environment for UML4SPM models (i.e. the Execution Model) can be generalised to any other MOF-instance language and is not restricted to UML-based languages.. The paper is organized as follows. Section 2 starts by motivating the use of UML 2.0 as a process modeling language. It highlights its strengths in terms of expressiveness but also its weaknesses such as the lack of an execution support and the inability of the standard to express some primary elements proper to process modeling. To overcome these limitations, an extension to UML is proposed through UML4SPM, our process modeling language. The executability issue is addressed by introducing the notion of the Execution Model in Section 3. Two realizations of the Execution Model in the context of UML4SPM are presented in section 4. Section 5 discusses the results of these realisations, gives the advantages and limitations of each one and synthesises the outcome of our experimentations. Related work is addressed in Section 6. Finally, section 7 sketches some perspectives and concludes this work. In this paper, we proposed an approach for building executable software process models. Additionally to coding team's best practices, process models can now be used for simulation and execution purposes. This would help not only for agent coordination, but also can be used as means to improve and to validate process definitions. Executability of models was addressed in the context of a software process modeling language (i.e., UML4SPM) thanks to the Execution Model approach. However, it can be generalized to any MOF-instance language. We provided two realizations of the Execution Model. The first one is Java using the visitor pattern. The second one, a more model-driven solution, is based on Kermeta and aspect modeling techniques. The outcome of this work is largely used by our industrial partners within the Modelplex projet. A larger evaluation of the use of UML4SPM in production stages is underway. In the context of process modeling, an important perspective of this work is the definition of the set of activities and constraints that would allow a process definition to be modified at runtime and without restarting the process execution i.e. preserving the process state. Through simulation and execution of software process models, the approach we propose provides project managers with earlier feedbacks on how the process should behave in production stages. It is particularly vital to evaluate process definitions carefully to be sure of their correctness and effectiveness. Important decisions on resource allocation, coordination of agents and procedural issues can then be taken before to put the process on rails. In the following we discuss the outcomes of our work and how they can be used in order to fulfill these expectations. In this section we only deal with UML-based process modeling languages, taxonomy of first-generation PMLs can be found in (Zameli and Lee 2001) .. In the industrial side, SPEM1.0 was the first standard SPML based on UML (UML1.4) (OMG SPEM1.0 2002). However SPEM1.0 has had a limited success within the industry since SPEM1.0 did not offer any execution support. Process models were only contemplative models. In SPEM2.0, the main advance was the proposition of a clear separation between the content of a method of its possible use within a specific process. SPEM2.0 extends the UML2.0 Infrastructure and does not use any concept from the UML2.0 Superstructure (i.e. Activities, Actions, etc.). Regarding executability, SPEM2.0 does provide neither concepts nor formalisms for executing process models. Instead, the standard proposes to either map process definitions into some project planning tools (e.g. MS. Project) which is not considered as process execution but a process planning activity or to define transformation rules into some business process execution languages (e.g. BPEL). Unfortunately, the standard does not define any of these rules.. In Di Nitto's et al. approach (Di Nitto et al. 2002) , authors aim at assessing the possibility of employing a subset of UML1.3 as an executable PML. It comprises two main phases. The first one consists in describing processes using UML diagrams. The second phase consists in translating these UML diagrams into code that can be enacted by the team's events-based workflow engine called OPSS. Process constituents can be defined by simply specializing a set of predefined classes provided by the approach in form of a UML class diagram. The flow of work is given in activity diagrams and the lifecycle of each entity is defined by a state machine. However, the activity and class diagrams have no links with each other. The approach does not extend the UML language nor introduces new concepts. Process elements are simply instances of the UML Class metaclass, which means that they all have the same semantics and notation as the UML Class metaclass. Regarding execution, it is essentially based on how state diagrams defined by the user are precise enough and sound in order to enable a complete code generation and to allow process execution within OPSS. Otherwise, code has to be added manually. The weak point in the executability aspect remains how information defined in activity diagrams (i.e., precedence between activities), state machines and class diagrams are integrated to generate each of the Java classes needed for the execution. Authors did not detail how this integration is realized.. Another approach, called Promenade (Franch and Rib 1998) , basically follows the same principle as DiNitto's. To model a process, one has to specialize the set of predefined classes provided by the approach. To define precedence between process's tasks, one has to define a precedence graph, which defines the order between all tasks of the process. However, authors do not specify how the precedence graph (including precedence rules) is to be integrated with the class diagram to form a complete process description. The approach does not provide any mechanism or way to execute Promenade process models. No tool or prototype was provided.. In (Chou and Chen 2000) , Chou proposed a software process modeling language consisting of high-level UML1.4-Based diagrams and a low-level process language. While UML diagrams are used for process's participants understanding, the process language is used to represent the process -from UML diagrams -in a machine-readable format i.e., a program. The principal obstacle of this approach is the lack of an automatic generation of process programs from UML diagrams, which imposes the rewriting of the process by developers mastering the proprietary OO language provided by the author.

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Extremes of spheroid shape factor based on two dimensional profiles The extremal shape factor of spheroidal particles is studied. Three dimensional particles are considered to be observed via their two dimensional profiles and the problem is to predict the extremal shape factor in a given size class. We proof the stability of the domain of attraction of the spheroid's and its profile shape factor under a tail equivalence condition. We show namely that the Farlie-Gumbel-Morgenstern bivariate distributions gives the tail uniformity. We provide a way how to find normalising constants for the shape factor extremes. The theory is illustrated on examples of distributions belonging to Gumbel and Frechet domain of attraction. We discuss the ML estimator based on the largest observations and hence the possible statistical applications at the end. In recent years the stereology of extremes is attracting more and more interest. The theoretical results and direct application to the material science can be seen e. g. in [3, 11, 12, 13] , where the extreme of the size in the so called Wicksell's corpuscle problem is studied. In a series of papers [7, 8, 9, 10] , e. g., we have discussed the extremes of the size or shape factor respectively for the oblate spheroids rather than for the balls. We continue in the paper [9] and in particular we complete the previous study for the prolate spheroids.. The main results of the paper are summarised in Theorems 1 and 4. The Maximum domain of attraction of the spheroid shape factor is shown to be 'translated' to the profiles under the tail uniformity condition. The tail uniformity condition is discussed briefly in Sections 3 and 5, for more detailed discussion see [10] .. The possible statistical application of the main results is described in Section 4. We conclude the paper in Section 5 giving some examples of the tail behaviour of the spheroid shape factor and its relation to the tail behaviour of the profile shape factor. Comparison of these two tail behaviours is an essential step toward the adjustment of the normalising constants which are needed for the prediction of the distribution of the shape factor extremes of spheroids based on the observation of the profile shape factor extremes.

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Impact of active thermal management on power electronics design Abstract Power electronic system design is typically constrained by the thermal limitation so by the overall losses and the peak current. To stay within the maximum current, reached only during transients, the system is typically overrated. Active thermal management is used to control the maximum temperature and the temperature swing to reduce failures that are mostly caused by them. In this paper it is proposed to use the active thermal management to reduce the switching losses or to move them to less stressed devices, during transients, such as a module can reach an higher current, without violating thermal constraints, and the need of overdesign can be reduced. Hence an optimal and cost effective design of power electronics system is achieved. PWM voltage source converters have become widely used in several applications like traction, automotive or the generation of renewable energies [1] , [2] . The design of the system has to be cost effective, guaranteeing reliability at the same time. However, overdesign is a common practice to reduce failures, especially during transients, avoiding too high temperatures or excessive thermal swings. This work proposes the use of a thermal management system not only for reducing failures related to overtemperature or temperature swings [3] , but also for achieving a loss reduction in transient conditions to enable a better utilization of the existing hardware. First, this work analytically analyzes thermal cycling of the junction temperature in an inverter and highlights how different operating conditions constrain the junction temperature. Practical examples how the thermal management system can control the losses with a benchmark of the possible stress reduction are given in chapter 4. Conclusions for system design with thermal management are given in chapter 5 and the results are summarized in chapter 6. A thermal management system enables loss redistribution and reduction. That can increase the overloading capability of power electronic modules, especially during transients, and facilitates good chip utilization without affecting the functionality. Using

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