Modular Filter and Source-Management Upgrade of RADAC

In an upgrade of the Range Data Acquisition Computer (RADAC) software, a modular software object library was developed to implement required functionality for filtering of flight-vehicle-tracking data and management of tracking-data sources. (The RADAC software is used to process flight-vehicle metric data for realtime display in the Wallops Flight Facility Range Control Center and Mobile Control Center.

Range Safety for an Autonomous Flight Safety System

The Range Safety Algorithm software encapsulates the various constructs and algorithms required to accomplish Time Space Position Information (TSPI) data management from multiple tracking sources, autonomous mission mode detection and management, and flight-termination mission rule evaluation. The software evaluates various user-configurable rule sets that govern the qualification of TSPI data sources, provides a prelaunch autonomous hold-launch function, performs the flight-monitoring-and-termination functions, and performs end-of-mission safin

Ant Colony Heuristic for Mapping and Scheduling Tasks and Communications on Heterogeneous Embedded Systems

To exploit the power of modern heterogeneous multiprocessor embedded platforms on partitioned applications, the designer usually needs to efficiently map and schedule all the tasks and the communications of the application, respecting the constraints imposed by the target architecture. Since the problem is heavily constrained, common methods used to explore such design space usually fail, obtaining low-quality solutions. In this paper, we propose an ant colony optimization (ACO) heuristic that, given a model of the target architecture and the application, efficiently executes both scheduling and mapping to optimize the application performance. We compare our approach with several other heuristics, including simulated annealing, tabu search, and genetic algorithms, on the performance to reach the optimum value and on the potential to explore the design space. We show that our approach obtains better results than other heuristics by at least 16% on average, despite an overhead in execution time. Finally, we validate the approach by scheduling and mapping a JPEG encoder on a realistic target architecture

Discrete and fuzzy dynamical genetic programming in the XCSF learning classifier system

A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to neural networks. This paper presents results from an investigation into using discrete and fuzzy dynamical system representations within the XCSF learning classifier system. In particular, asynchronous random Boolean networks are used to represent the traditional condition-action production system rules in the discrete case and asynchronous fuzzy logic networks in the continuous-valued case. It is shown possible to use self-adaptive, open-ended evolution to design an ensemble of such dynamical systems within XCSF to solve a number of well-known test problems

Learning Mazes with Aliasing States: An LCS Algorithm with Associative Perception

Learning classifier systems (LCSs) belong to a class of algorithms based on the principle of self-organization and have frequently been applied to the task of solving mazes, an important type of reinforcement learning (RL) problem. Maze problems represent a simplified virtual model of real environments that can be used for developing core algorithms of many real-world applications related to the problem of navigation. However, the best achievements of LCSs in maze problems are still mostly bounded to non-aliasing environments, while LCS complexity seems to obstruct a proper analysis of the reasons of failure. We construct a new LCS agent that has a simpler and more transparent performance mechanism, but that can still solve mazes better than existing algorithms. We use the structure of a predictive LCS model, strip out the evolutionary mechanism, simplify the reinforcement learning procedure and equip the agent with the ability of associative perception, adopted from psychology. To improve our understanding of the nature and structure of maze environments, we analyze mazes used in research for the last two decades, introduce a set of maze complexity characteristics, and develop a set of new maze environments. We then run our new LCS with associative perception through the old and new aliasing mazes, which represent partially observable Markov decision problems (POMDP) and demonstrate that it performs at least as well as, and in some cases better than, other published systems

Sustainability perspectives: a new methodological approach for quantitative assessment

This paper proposes a new tool to assess sustainability and make the concept of sustainable development operational. It considers its multi-dimensional structure combining the information deriving from a selection of relevant sustainability indicators belonging to economic, social and environmental pillars. The main novelties of this approach are the modelling framework, a recursive-dynamic computable general equilibrium used to calculate the trend of all indicators over time throughout the world, and the aggregation methodology to reconcile them in one aggregate index to measure overall sustainability. The former allows capturing the sector and regional interactions and higher-order effects driven by background assumptions on relevant variables to depict future scenarios. The latter makes it possible to compare sustainability performances, under alternative scenarios, across countries and over time. Main results show that the current sustainability at world level differs from what the traditional measure of well-being, the GDP, depicts, highlighting the trade-offs among different components of sustainability. Moreover, in the next decade a slight decrease in world sustainability may occur, in spite of an expected increase in world domestic product. Finally, dedicated policies increase overall sustainability, showing that social and environmental benefits may be greater than the correlated economic costs

Diatom extraction: A new technique with heated H2O2. A technical note

The best method of diatom identification in animal and human tissues is still an important discussion topic, in terms of effectiveness and reliability. In this technical note, authors propose a new method of extraction of diatoms using heated hydrogen peroxide from animal and human tissue samples. This method has been compared with the traditional method of digestion with acids. The results of the comparison show that heated hydrogen peroxide extraction is more efficient in terms of reduction of sediment, extraction of the material and preservation of diatoms proving to be a viable alternative to conventional approaches with acids in terms of costs and operator safety

CANNABINOID-INDUCED PSYCHOSIS: A CROSS-SECTIONAL GENDER STUDY

Background: Gender is a crucial factor in the development of mental illnesses, with an essential influence on clinical characteristics and not only on the prevalence of each disorder. Gender differences in cannabinoid-related disorders are highlighted by different research fields (preclinical, clinical, socio-demographic studies), but few studies focused on differential symptom expression in cannabinoid-induced psychosis. This study aims at investigating qualitative and quantitative gender differences in specific psychopathological domains in a clinical sample of subjects affected by cannabinoid-induced psychotic disorder, without psychiatric comorbidity. Subjects and methods: The study was carried out at the Psychiatric Inpatient Service of General Hospital of Perugia (Italy). In this cross-sectional gender study, 28 inpatients were enrolled, 14 males (M) and 14 females (F). Participants were administered a psychometric battery consisting of 7 tests (PANSS, NDS-I, YMRS, HAM-D, HAM-A, AQ, SSI) in order to investigate 7 psychopathological domains (Psychosis, Dysphoria, Mania, Depression, Anxiety, Aggressive Behaviour and Suicide Ideation). Scores obtained at each test were compared between male and females by using Mann-Whitney U test (p<0.05). Results: In this study, we observed that males present higher severity of psychotic symptoms, with prominent scores in PANSS positive and general psychopathology scale (p<0.001), and an important expression of aggressive behavior (p<0.001) compared with females. Female sample, instead, shows a greater expression of dysphoria and depressive domains (p<0.001) and a lower, but statistically significant, prevalence in the anxiety domains expression (p=0.01). By these observations, we could assert that in male group thought disorders are prominent. On the other hand, in female group affective disorder are prominent. Conclusions: This study confirmed how gender influences the phenomenic expression of psychiatric disorders. In line with the precision medicine paradigm, a further clarification of different clinical profiles based on gender would allow the choice of a personalized treatment plan with better efficacy and accuracy indices