Designing fuzzy rule based classifier using self-organizing feature map for analysis of multispectral satellite images

We propose a novel scheme for designing fuzzy rule based classifier. An SOFM based method is used for generating a set of prototypes which is used to generate a set of fuzzy rules. Each rule represents a region in the feature space that we call the context of the rule. The rules are tuned with respect to their context. We justified that the reasoning scheme may be different in different context leading to context sensitive inferencing. To realize context sensitive inferencing we used a softmin operator with a tunable parameter. The proposed scheme is tested on several multispectral satellite image data sets and the performance is found to be much better than the results reported in the literature.Comment: 23 pages, 7 figure

Estimating Fire Weather Indices via Semantic Reasoning over Wireless Sensor Network Data Streams

Wildfires are frequent, devastating events in Australia that regularly cause significant loss of life and widespread property damage. Fire weather indices are a widely-adopted method for measuring fire danger and they play a significant role in issuing bushfire warnings and in anticipating demand for bushfire management resources. Existing systems that calculate fire weather indices are limited due to low spatial and temporal resolution. Localized wireless sensor networks, on the other hand, gather continuous sensor data measuring variables such as air temperature, relative humidity, rainfall and wind speed at high resolutions. However, using wireless sensor networks to estimate fire weather indices is a challenge due to data quality issues, lack of standard data formats and lack of agreement on thresholds and methods for calculating fire weather indices. Within the scope of this paper, we propose a standardized approach to calculating Fire Weather Indices (a.k.a. fire danger ratings) and overcome a number of the challenges by applying Semantic Web Technologies to the processing of data streams from a wireless sensor network deployed in the Springbrook region of South East Queensland. This paper describes the underlying ontologies, the semantic reasoning and the Semantic Fire Weather Index (SFWI) system that we have developed to enable domain experts to specify and adapt rules for calculating Fire Weather Indices. We also describe the Web-based mapping interface that we have developed, that enables users to improve their understanding of how fire weather indices vary over time within a particular region.Finally, we discuss our evaluation results that indicate that the proposed system outperforms state-of-the-art techniques in terms of accuracy, precision and query performance.Comment: 20pages, 12 figure

Programming multi-level quantum gates in disordered computing reservoirs via machine learning and TensorFlow

Novel machine learning computational tools open new perspectives for quantum information systems. Here we adopt the open-source programming library TensorFlow to design multi-level quantum gates including a computing reservoir represented by a random unitary matrix. In optics, the reservoir is a disordered medium or a multi-modal fiber. We show that trainable operators at the input and the readout enable one to realize multi-level gates. We study various qudit gates, including the scaling properties of the algorithms with the size of the reservoir. Despite an initial low slop learning stage, TensorFlow turns out to be an extremely versatile resource for designing gates with complex media, including different models that use spatial light modulators with quantized modulation levels.Comment: Added a new section and a new figure about implementation of the gates by a single spatial light modulator. 9 pages and 4 figure

Semantic and inferencing abilities in children with communication disorders

Background: Semantic and inferencing abilities have not been fully examined in children with communication difficulties. Aims: To investigate the inferential and semantic abilities of children with communication difficulties using newly designed tasks. Methods & Procedures: Children with different types of communication disorder were compared with each other and with three groups of typically developing children: those of the same chronological age and two groups of younger children. In total, 25 children aged 11 years with specific language impairment and 22 children, also 11 years of age, with primary pragmatic difficulties were recruited. Typically developing groups aged 11 (n = 35; age‐match), and those aged 9 (n = 40) and 7 (n = 37; language similar) also participated as comparisons. Outcomes & Results: For Semantic Choices, children with specific language impairment performed significantly more poorly than 9‐ and 11‐year‐olds, whilst the pragmatic difficulties group scored significantly lower than all the typically developing groups. Borderline differences between specific language impairment and pragmatic difficulties groups were found. For inferencing, children with communication impairments performed significantly below the 11‐year‐old peers, but not poorer than 9‐ and 7‐year‐olds, suggesting that this skill is in line with language ability. Six children in the pragmatic difficulties group who met diagnosis for autism performed more poorly than the other two clinical groups on both tasks, but not statistically significantly so. Conclusions: Both tasks were more difficult for those with communication impairments compared with peers. Semantic but not inferencing abilities showed a non‐significant trend for differences between the two clinical groups and children with pragmatic difficulties performed more poorly than all typically developing groups. The tasks may relate to each other in varying ways according to type of communication difficulty

Semantic and inferencing abilities in children with communication disorders

Background: Semantic and inferencing abilities have not been fully examined in children with communication difficulties. Aims: To investigate the inferential and semantic abilities of children with communication difficulties using newly designed tasks. Methods & Procedures: Children with different types of communication disorder were compared with each other and with three groups of typically developing children: those of the same chronological age and two groups of younger children. In total, 25 children aged 11 years with specific language impairment and 22 children, also 11 years of age, with primary pragmatic difficulties were recruited. Typically developing groups aged 11 (n = 35; age‐match), and those aged 9 (n = 40) and 7 (n = 37; language similar) also participated as comparisons. Outcomes & Results: For Semantic Choices, children with specific language impairment performed significantly more poorly than 9‐ and 11‐year‐olds, whilst the pragmatic difficulties group scored significantly lower than all the typically developing groups. Borderline differences between specific language impairment and pragmatic difficulties groups were found. For inferencing, children with communication impairments performed significantly below the 11‐year‐old peers, but not poorer than 9‐ and 7‐year‐olds, suggesting that this skill is in line with language ability. Six children in the pragmatic difficulties group who met diagnosis for autism performed more poorly than the other two clinical groups on both tasks, but not statistically significantly so. Conclusions: Both tasks were more difficult for those with communication impairments compared with peers. Semantic but not inferencing abilities showed a non‐significant trend for differences between the two clinical groups and children with pragmatic difficulties performed more poorly than all typically developing groups. The tasks may relate to each other in varying ways according to type of communication difficulty

A High Performance Fuzzy Logic Architecture for UAV Decision Making

The majority of Unmanned Aerial Vehicles (UAVs) in operation today are not truly autonomous, but are instead reliant on a remote human pilot. A high degree of autonomy can provide many advantages in terms of cost, operational resources and safety. However, one of the challenges involved in achieving autonomy is that of replicating the reasoning and decision making capabilities of a human pilot. One candidate method for providing this decision making capability is fuzzy logic. In this role, the fuzzy system must satisfy real-time constraints, process large quantities of data and relate to large knowledge bases. Consequently, there is a need for a generic, high performance fuzzy computation platform for UAV applications. Based on Lees’ [1] original work, a high performance fuzzy processing architecture, implemented in Field Programmable Gate Arrays (FPGAs), has been developed and is shown to outclass the performance of existing fuzzy processors

Investigating the dual function of gesture in blind and visually impaired children. (Poster)

Co-speech gesture research explores the role of gesture in communication, i.e. whether gestures are intended for the listener/audience (e.g. Mol et al. 2009; Alibali et al., 2001; Holler & Beattie, 2003) or support the process of speech production (Kita & Davies, 2009; Hostetter et al. 2007). To investigate the role of gesture in communication we turn to blind and visually impaired speakers whose opportunities to learn gestures visually are limited (cf. Iverson & Goldin-Meadow 1998; 2001). The present study aims at providing insight into the nature and occurrence of co-speech gestures in spontaneous speech: between blind, severely visually impaired and sighted individuals. Participants were asked to read a short story (either in print or in Braille) and to re-tell it to the interviewer. Care was taken to establish an environment in which the participants would feel safe and would not refrain from gesturing for fear of hurting themselves or others. We predicted that if blind speakers did not gesture as much as their visually impaired peers it would suggest that gesture is to some extent acquired through visual instruction. However, following Iverson et al. (2000) and Iverson and Goldin-Meadow (1998) we hypothesized that despite the absence of visual gestural stimuli during the language-learning process gesture is present in the language of the blind participants - but there would be differences in gesture form, types and functions. The present study aims at exploring and categorizing these differences, with regard to how sensory references are visible in the gestures of participants with various degrees of sight impairment. Regardless of dissimilarities, the presence of gesture in both the blind and impaired individuals points towards a dual function of co-speech gestures, i.e. a device for both the speaker and their interlocutor