MASTER SLEUTHS- REVISED

After eating humble pie, I turned it down. Master doesn't let you do that. Thanks, then I'll turn it off too. Having a clock isn't making it funnier. There isn't much point is using the harder setting since there are no difficulty mode achievements for the game. Originally posted by Spatz:. Last edited by zounds ; 13 Jun, 5: Slope parameters were set to 30 and 20 for the slope coefficient and critical slope respectively and the distance of influence of roads set to 5 pixels. These parameters remain unchanged over the various simulations made. Each experiment was run 30 times.

Variations are shown in graphs using specific indicators. As variations are small, the spatial analysis of urban growth is made for one simulation.

A scenario was defined based on the urban changes that occurred between and Urban pattern parameters were empirically determined using GIS and landscape metrics. Based on the map of urban changes, it is possible to approximate which proportion of the changes are located near roads or existing urban land use in Urban patch size in cells allows us to differentiate their respective contribution: This simple method, which cannot distinguish the merging of small urban patches with bigger, leads to the following approximate combination for growth during The patch cohesion increases as the patch type becomes more clumped or aggregated in its distribution; hence, more physically connected Gustafson, An additional method was used in the assessment.

Maps of pixel-by-pixel differences between simulated and observed maps for were computed for assessing the location disagreement Pontius , , i. The simulations S1 used the land cover map of as the input map. They then run until and the output maps were compared with the observed map. Parameters used are summarized in table 1. Table 1 — Summary of the validation experiments.

Cited excluded and attractiveness maps are described in figure 4. A scenario exhibiting contrasting changes in terms of land demand, urban patterns and land planning strategies excluded maps is defined and simulated. The retained assumptions were exaggerated for the sake of the demonstration. Three sub-periods were defined: Municipalities located further away from Toulouse city and its surrounding municipalities become increasingly attractive considering the attractiveness of rural areas Attractiveness map A2 — Fig.

In parallel, the peak oil scenario induces a strong increase in transportation costs reducing the attractiveness of rural municipalities Attractiveness map A3 - Fig. The input parameters are summarized in table 2. Urban dynamics are illustrated by simulated urban maps and were monitored over the period by using various spatial metrics: Figure 4 — Additional maps used for the scenarios: This directly influences the mean distance between patches that is closer to the value observed in The mean variation encompasses the value of although those from the neutral simulations strongly differ.

Results are obtained for the mean patch size PA show great similarities between the observation in and the simulations S1a and S1b.

• Introducing Penny Dreadnought, Insidious Indoctrination Engine of the Abominable Gentlemen.
• Stephen Jones: Dark Detectives: Adventures of the Supernatural Sleuths ()!
• as master sleuth - definition - English!

Results from S1a are closer than those from S1B. The Cohesion and Clumpy indices show similar results. Comparison with S1c null model shows that results obtained from simulation S1a and S1b are closer to the observed values than those provided by randomness. Table 2 — Comparison of simulated and observed urban areas using landscape metrics. The deviation are computed from the 30 simulations made for each simulation. They respectively exhibit Urbanization is better predicted in S1a in the central part of the study area while the simulation of urban growth is better in remote areas for S1b.

Conversely, these simulations respectively over-estimate and under-estimate in the central area. Adding an additional help to improve its predictive power, i. Figure 5 — Difference maps between observed urban extent in and the simulated urban growth for a using the attractiveness map A1 and b without using the attractiveness map A1. Four classes can be distinguished: When the main trend of urban growth rates assumes a linear increase Fig.

For example, the increase of the number of urban patches from to involving a higher rate of spontaneous growth from 7, to 26, patches - Fig. This trend breaking of urban patterns during the simulation can be observed as well with the mean patch area Fig. Indeed, while the urban growth is characterized by small and scattered patches over decreasing the mean distance between patches Fig.

Stochastic processes do not strongly affect the results: In others words, trend-breaking are under control by the model and does not inherit from randomness. Figure 7 — Evolution of a the overall urban area in ha ; b the number of urban patches; c the mean urban patch size and its standard deviation; d the mean distance between urban patches and its standard deviation. The error bars illustrate the mean deviation for the concerned indicators computed from the 30 simulations made.

Sleuth on the Goose - Baobab Press

The scenarios defined then combine both normative assumptions from narratives defining which kind of urban form we want to? The participatory approach involved scientists, experts, urban planners and decision makers and led to the definition of seven future scenarios. Urban growth is authorized only in nearby existing urban areas.

The demographic trend is similar to the previous scenario. Unfortunately, in this scenario local authorities did not anticipate the peak oil crisis occurring in and the main industries aeronautics and space industries are particularly affected. NEDUM driven by economic considerations and general laws that make the model robust and suitable for long-term simulations 5.

However, the model exhibits some limitations in simulating small-scale details e. For the reactive scenario, NEDUM expects a loss of population leading to negative rates of urban growth. The dynamics of urban growth for these three scenarios are illustrated by simulated urban maps and various spatial metrics over the period: Table 3 — Summary of the application experiments. These maps integrate the feedback effects of newly urbanized areas during the preceding period.

The increase of the mean distance between urban patches illustrates a dispersive growth from to Then it reaches a threshold beyond which it shows a densification of the scattered urban patches Fig. Considering that the passive scenario projects current urban planning norms defined by stakeholders and aiming at controlling the scattered urban sprawl, results show that these norms are not efficient to reach this objective. Hence, the urban strategies i.

This scenario illustrates a reaction by decision makers, occurring in , towards addressing the inefficiency of current urban planning strategies. While new strategies aimed at moving towards a more compact urban area, the simulated map for Fig. The number, the mean area and the mean distance between urban patches remain approximately constant after Fig. Even if decision makers have been reactive in managing their urban areas according to a common vision, the lack of anticipation of global socio-economic events and their related regional effects lead to inefficient urban policies.

Another scenario not shown here , combining the demographic trends of the two previous scenarios with the reactive one, illustrates inversely their efficiency but only for a year period. Because the green belt footprint has not been modified between and , the growth leads to new urbanized areas farther away, illustrating an unexpected consequence of the green-belt. Figure 8 — Simulation of urban growth in red compared to the urban extent in in grey for three contrasting scenarios.

Evolution over the simulation period of the evaluation criteria for the passive plain line , the green dot line and the reactive dash line scenarios. The error bars illustrates the mean deviation computed from the 30 simulations made. Based on these assumptions, how can a model be validated? How can these performances be evaluated?

Even if this critical issue has not been directly answered, the originality of this paper comes from the proposed validation framework which combines three experiments and multiple evaluation indices. Taken independently, these experiments may appear odd or even trivial or tautological. But, if the model is able to simulate past changes, it does not automatically mean that it is able to simulate future scenario-based changes that did not occur yet in the past.

Sleuth on the Goose

Moreover, we hypothesize that conventional validation tools Paegelow et al, are consistent for validating the use of a model within a prospective approach Houet et al, ; Houet, if several of them are combined. A single tool may not be appropriate to evaluate all the experiments. Concerning the model calibration, we could have used the original version of SLEUTH to calibrate the input parameters. When considering that assessing the simulation of the future of urban change is not possible, it may slightly balance the level of requirements that modelers may have for the input parameters.

The more precise the input data, the more confident the users are in the resulting simulations. The final point concerns the robustness of the results. As shown in table 4, figures 7 and 8, small variations can be observed from the 30 simulations made. They inherits from the stochastic allocation processes. Results show that randomness does not affect the trajectories of scenario-based urban changes are helpful to improve the confidence users can have in the model outcomes.

The first concerns the influence of the attractiveness map. Results obtained from the simulation of past urban evolution show some controversial effects of this optional additional factor. The visual comparison of difference maps Fig. The integration of the economic driving factor is particularly valuable. Better performance could have been obtained by tuning the growth parameters, whose relative contributions may differ if using this optional map. However, the aim was to assess model performance using similar parameters values that can be derived from various simple — GIS, expert-based or scenario-based — approaches as shown with the other two experiments.

The SAS approach requires it to be simple and flexible when used within a participatory framework, as well as sophisticated when tightly coupled with other models. Hence, even if some parameters are empirically calibrated, the resulting simulations still provide valuable urban maps. The main difference between them was the way that they are used and parameterized for exploring the future: SLEUTH is valuable for exploring future urban trends of urban dynamics, based on a robust calibration phase, coupled or not with the various urban planning strategies.

Yes The model calibration and the auto-adaptation of growth parameters using landscape patterns indices allow the simulation over several centuries with high accuracy. Clarke and Gaydos ; Dietzel and Clarke Yes Probably limited to a short period years due the empirically defined growth parameters. Auto-adaptive growth parameters allow the simulation of trend breaking of the urban patterns, with no disruptions in the land demand. Auto-adaptation is by self-modification.

Clarke and Gaydos Users empirically control the contribution of each parameters land demand, growth parameters… over user-defined sub-periods. Adapted to simulate narratives, normative and forecasting scenarios. Main limitations concern the GIS database preparation. The calibration is time consuming. She wrote murder who-done-its by profession, but always seemed to stumble into murder investigations as well; whether while travelling extensively around the country, or at home in Cabot Cove, Maine.

1. translation and definition "as master sleuth", Dictionary English-English online?
2. Destinys Journey [Destinies 2] (Siren Publishing Menage and More ManLove).
3. Côte dIvoire: Du schéol à lexpectative... (Essai t. 1) (French Edition).
4. Navigation.
5. Warrior Soul!
6. The V8 Sleuth // V8 Sleuth News // TOURING CAR MASTERS RETURN TO MUSCLE CAR MASTERS.

Jessica is a great detective not only because she deduces clues based on happenstance and observation, but because she is a witty and interesting person with a penchant for the macabre. Nancy Drew is one of the most famous girl detectives, and for good reason. Nancy first appeared in in a series of mystery novels written by various people under the pseudonym of Carolyn Keene. Since that initial series Nancy has been revamped various times for everything from seventies TV series to made-for-TV movies and modern book series.

The version of the books I read as a little girl was the revised versions, bound in yellow with hand drawn covers. Nancy is a great detective, who often uncovers stolen objects or missing people with the help of her female friends Bess and George, her boyfriend Ned, or her father, Carson.

Did You Know?

She is headstrong, smart, and a major sleuth, making her an optimal role model for young girls. Bell would go on to portray the character in a movie of the same name in , and Thomas has gone on to write two novels with the female detective published in and respectively. Veronica is sarcastic, resourceful, and super smart, making her not only a great detective but a figure most people would love to emulate.

Her partner Seeley is much more impressed with intuition and good solid police work. Brennan is a great detective because she utilizes the medical field to solve both new and old mysteries and does it because she cares about the victims of crimes ranging from murder to genocide. While Nancy Drew is much more mature and older, Trixie is still a girl, and so much of her troubles stem from school, minor adventures, and general shenanigans. Her series ran from and her mysteries often deal in missing property, missing people, and also feature travels by the Belden clan.

Trixie is a strong-willed yet young presence who solves mysteries with solid deduction and skill. While many female detectives get their man by pure observation, Olivia Benson utilizes a realistic set of procedures and police work. She is the product of rape, and her mother dies from falling down some stairs due to her alcoholism. She is one of the strongest women on television and is a great detective who tracks leads, interviews perps, and has been a part of multiple hostage negotiation efforts.

Many of the mysteries that she deals in have to do with the Los Angeles setting of the show, meaning they involve gang violence, drugs, human trafficking, and corruption. Johnson is seen as a disorganized, often neurotic mess when it comes to her personal life, but is a surefire investigator and boss who always goes for the jugular in the interrogation room.

Jane Marple was created by the enigmatic Agatha Christie in a series of twelve novels and twenty short stories. Marple is a shrewd intellectual who always sees the negative side of humanity, and relates snatches of conversation to cases that she is working on. Her greatest characteristic is her advanced age, which often means she is disparaged by relatives and acquaintances alike, which makes it easy for her to make herself at home with everyone from townspeople to aristocracy.