Visual Motor Integration and relationship to the level of Processing Speed Index among students with Learning Disabilities

The study aim of this research was to determine (Visual Motor Integration, VMI) and its relationship to the level of (Processing Speed Index, PSI) in students with (LD). To achieve the study's objectives, the correlative descriptive method was used. The study comprised (100) Saudi students, including (50) students with (LD) and (50) normal students. Their ages ranged from 8 to 13 years. A Wechsler Scale-4 was also employed. The content validity and concurrent validity of the (cancellation) test in its two sub-categories (Random and Regular) was (80%), and the construct validity was greater than (0.30). The correlation between the sub-tests (Random and Regular) and the total score of the (VMI) test was 0.934-0.937), And for normal students are (0.965, 0.920). The construct validity of the values of the correlation coefficients between the sub-tests and the total score of the (PSI) test was higher than (0.30), and the correlation through the construct validity of the (PSI) test among students (LD), with the (PSI) among normal students. the correlation coefficients for the sub-tests (Coding and Symbol Search) were (0.770, 0.474). and for normal students (0.820, 0.876).       Indications of the (VMI) test's reliability were also obtained through the Content Validity test (Cancellation) with its two branches (Random and Regular) using Cronbach's alpha coefficient (0.700). The reliability of the (PSI) test was determined using the internal consistency method and Cronbach's alpha test (0.825). The study's findings revealed that the level of (VMI) (cancellation) and (PSI) of (LD) students was extremely low. In addition, no statistically significant relationship exists between (VMI) and (PSI) levels. There were also statistically significant differences in the level of (VMI) due to age in favor of (LD) students in the age group (11–13). There were no statistically significant differences in the level of (VMI) compared to the (Regular) test among students with (LD). There were also statistically significant differences in total intelligence (PSI) levels due to variable students (LD and normal), with an arithmetic mean for (LD) students (65.06) and an arithmetic mean for normal students (101.06).   The study recommends teachers' awareness of the importance of (VMI) intelligence in the (LD) category and conducting studies comparing (PSI) intelligence with the Mild Intellectual Disability category

Modelling Socially Intelligent Agents

The perspective of modelling agents rather than using them for a specificed purpose entails a difference in approach. In particular an emphasis on veracity as opposed to efficiency. An approach using evolving populations of mental models is described that goes some way to meet these concerns. It is then argued that social intelligence is not merely intelligence plus interaction but should allow for individual relationships to develop between agents. This means that, at least, agents must be able to distinguish, identify, model and address other agents, either individually or in groups. In other words that purely homogeneous interaction is insufficient. Two example models are described that illustrate these concerns, the second in detail where agents act and communicate socially, where this is determined by the evolution of their mental models. Finally some problems that arise in the interpretation of such simulations is discussed

An Individual-based Probabilistic Model for Fish Stock Simulation

We define an individual-based probabilistic model of a sole (Solea solea) behaviour. The individual model is given in terms of an Extended Probabilistic Discrete Timed Automaton (EPDTA), a new formalism that is introduced in the paper and that is shown to be interpretable as a Markov decision process. A given EPDTA model can be probabilistically model-checked by giving a suitable translation into syntax accepted by existing model-checkers. In order to simulate the dynamics of a given population of soles in different environmental scenarios, an agent-based simulation environment is defined in which each agent implements the behaviour of the given EPDTA model. By varying the probabilities and the characteristic functions embedded in the EPDTA model it is possible to represent different scenarios and to tune the model itself by comparing the results of the simulations with real data about the sole stock in the North Adriatic sea, available from the recent project SoleMon. The simulator is presented and made available for its adaptation to other species.Comment: In Proceedings AMCA-POP 2010, arXiv:1008.314

Quantifying sources of uncertainty in regional climate model scenarios for Ireland

This thesis develops a novel framework for model skill assessment and the generation of probabilistic future climate scenarios. Traditional approaches to model validation assume that skill in simulating the mean climate is a valid indicator of skill in modelling the climate system. However, without information about how errors arise, conclusions cannot be drawn about whether models are genuinely skilful. Initially, verification statistics are used to assess model skill in simulating seasonal means and variability of Irish climate for 1961-1990. Significant biases were identified, however without further analysis, these biases cannot be attributed to a cause. Therefore, a spatial analysis, including EOF analysis, was undertaken which indicated that biases may be either spatially consistent (systematic) or inconsistent (random), an important distinction. Next, representation of a key large-scale driver of Irish climate, the North Atlantic Oscillation, was examined for a representative subsample of models. Skill in simulating the NAO was found to vary considerably between models. Therefore, assessing statistics of mean climate may not be the optimum way to characterize model skill, as deficiencies in the representation of large-scale drivers may not be detected. Both quantitative and qualitative information from the skill assessments was used to inform probabilistic ensemble projections of future climate using Bayesian Model Averaging. In some cases, weighting scheme variation affects the ensemble PDF shape. In other cases, PDFs are similar when different weights are used, but the relative contributions of ensemble members vary. This is a crucial finding, as this underlying variation may not be immediately apparent, but may affect the confidence attached to the PDF. Therefore, robustness of ensemble generation methods must be considered when determining the level of confidence attached to a projection. Finally, the implications of these results for climate decision-making are discussed and recommendations for the use of climate models in decision-making are presented

A methodology for realistic space launch risk estimation using information-fusion-based metric

In light of the significant changes being observed in the US space industry, in terms of the increase share of commercial launches, the development of inland spaceports, and the emergence of new vehicle designs and propulsion systems, there is need to reassess launch safety. In this paper, several issues related to space launch safety are reviewed, one in particular being the use, as the main the safety metric, of the mean collective risk to the general public, also known as the expectation of casualties. A new, decision level, information-fusion-based metric is proposed, and through a detailed case study, its merit in terms of the quality and quantity of information it generates is illustrated. The need for a new metric is here advocated as a critical first step toward the necessary transition from a risk avoidance philosophy to space launch safety to a risk management philosophy

Comparing software prediction techniques using simulation

The need for accurate software prediction systems increases as software becomes much larger and more complex. We believe that the underlying characteristics: size, number of features, type of distribution, etc., of the data set influence the choice of the prediction system to be used. For this reason, we would like to control the characteristics of such data sets in order to systematically explore the relationship between accuracy, choice of prediction system, and data set characteristic. It would also be useful to have a large validation data set. Our solution is to simulate data allowing both control and the possibility of large (1000) validation cases. The authors compare four prediction techniques: regression, rule induction, nearest neighbor (a form of case-based reasoning), and neural nets. The results suggest that there are significant differences depending upon the characteristics of the data set. Consequently, researchers should consider prediction context when evaluating competing prediction systems. We observed that the more "messy" the data and the more complex the relationship with the dependent variable, the more variability in the results. In the more complex cases, we observed significantly different results depending upon the particular training set that has been sampled from the underlying data set. However, our most important result is that it is more fruitful to ask which is the best prediction system in a particular context rather than which is the "best" prediction system

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.