816 resultados para Embedded System, Domain Specific Language (DSL), Agenti BDI, Arduino, Agentino
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The aim of the present study was to compare the motor function of a clinical sample of children with specific language impairment (SLI) to a language-matched comparison group that had not been referred for SLI assessment. A typical language comparison group with similar nonverbal IQ was also included. There were approximately 35 children in each group, aged 9- to 10-years-old, and the children completed a range of standardised language, motor and literacy measures. The results showed that the SLI group scored significantly lower than the language-matched and typical language comparison groups on all of the motor and literacy measures. We conclude that language factors alone are insufficient to explain the extensive comorbid motor and literacy deficits shown by the children with SLI in this study. We suggest that the clinical diagnosis of SLI may be influenced by the presence of additional developmental difficulties, which should be made explicit in assessment procedures, and that intervention strategies which address the broad range of difficulties experienced by children with a clinical diagnosis of SLI, should be prioritised.
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Technical market indicators are tools used by technical an- alysts to understand trends in trading markets. Technical (market) indicators are often calculated in real-time, as trading progresses. This paper presents a mathematically- founded framework for calculating technical indicators. Our framework consists of a domain specific language for the un- ambiguous specification of technical indicators, and a run- time system based on Click, for computing the indicators. We argue that our solution enhances the ease of program- ming due to aligning our domain-specific language to the mathematical description of technical indicators, and that it enables executing programs in kernel space for decreased latency, without exposing the system to users’ programming errors.
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Eye-tracking studies have shown how people with autism spend significantly less time looking at socially relevant information on-screen compared to those developing typically. This has been suggested to impact on the development of socio-cognitive skills in autism. We present novel evidence of how attention atypicalities in children with autism extend to real-life interaction, in comparison to typically developing (TD) children and children with specific language impairment (SLI). We explored the allocation of attention during social interaction with an interlocutor, and how aspects of attention (awareness checking) related to traditional measures of social cognition (false belief attribution). We found divergent attention allocation patterns across the groups in relation to social cognition ability. Even though children with autism and SLI performed similarly on the socio- cognitive tasks, there were syndrome-specific atypicalities of their attention patterns. Children with SLI were most similar to TD children in terms of prioritising attention to socially pertinent information (eyes, face, awareness checking). Children with autism showed reduced attention to the eyes and face, and slower awareness checking. This study provides unique and timely insight into real-world social gaze (a)typicality in autism, SLI and typical development, its relationship to socio-cognitive ability, and raises important issues for intervention.
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Product Line software Engineering depends on capturing the commonality and variability within a family of products, typically using feature modeling, and using this information to evolve a generic reference architecture for the family. For embedded systems, possible variability in hardware and operating system platforms is an added complication. The design process can be facilitated by first exploring the behavior associated with features. In this paper we outline a bidirectional feature modeling scheme that supports the capture of commonality and variability in the platform environment as well as within the required software. Additionally, 'behavior' associated with features can be included in the overall model. This is achieved by integrating the UCM path notation in a way that exploits UCM's static and dynamic stubs to capture behavioral variability and link it to the feature model structure. The resulting model is a richer source of information to support the architecture development process.
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Thesis submitted in the fulfilment of the requirements for the Degree of Master in Electronic and Telecomunications Engineering
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Thylakoid membrane fractions were prepared from specific regions of thylakoid membranes of spinach (Spinacia oleracea). These fractions, which include grana (83), stroma (T3), grana core (8S), margins (Ma) and purified stroma (Y100) were prepared using a non-detergent method including a mild sonication and aqueous two-phase partitioning. The significance of PSlla and PSII~ centres have been described extensively in the literature. Previous work has characterized two types of PSII centres which are proposed to exist in different regions of the thylakoid membrane. a-centres are suggested to aggregate in stacked regions of grana whereas ~-centres are located in unstacked regions of stroma lamellae. The goal of this study is to characterize photosystem II from the isolated membrane vesicles representing different regions of the higher plant thylakoid membrane. The low temperature absorption spectra have been deconvoluted via Gaussian decomposition to estimate the relative sub-components that contribute to each fractions signature absorption spectrum. The relative sizes of the functional PSII antenna and the fluorescence induction kinetics were measured and used to determine the relative contributions of PSlla and PSII~ to each fraction. Picosecond chlorophyll fluorescence decay kinetics were collected for each fraction to characterize and gain insight into excitation energy transfer and primary electron transport in PSlla and PSII~ centres. The results presented here clearly illustrate the widely held notions of PSII/PS·I and PSlIa/PSII~ spatial separation. This study suggests that chlorophyll fluorescence decay lifetimes of PSII~ centres are shorter than those of PSlIa centres and, at FM, the longer lived of the two PSII components renders a larger yield in PSlIa-rich fractions, but smaller in PSIlr3-rich fractions.
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This work is aimed at building an adaptable frame-based system for processing Dravidian languages. There are about 17 languages in this family and they are spoken by the people of South India.Karaka relations are one of the most important features of Indian languages. They are the semabtuco-syntactic relations between verbs and other related constituents in a sentence. The karaka relations and surface case endings are analyzed for meaning extraction. This approach is comparable with the borad class of case based grammars.The efficiency of this approach is put into test in two applications. One is machine translation and the other is a natural language interface (NLI) for information retrieval from databases. The system mainly consists of a morphological analyzer, local word grouper, a parser for the source language and a sentence generator for the target language. This work make contributios like, it gives an elegant account of the relation between vibhakthi and karaka roles in Dravidian languages. This mapping is elegant and compact. The same basic thing also explains simple and complex sentence in these languages. This suggests that the solution is not just ad hoc but has a deeper underlying unity. This methodology could be extended to other free word order languages. Since the frame designed for meaning representation is general, they are adaptable to other languages coming in this group and to other applications.
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Malayalam is one of the 22 scheduled languages in India with more than 130 million speakers. This paper presents a report on the development of a speaker independent, continuous transcription system for Malayalam. The system employs Hidden Markov Model (HMM) for acoustic modeling and Mel Frequency Cepstral Coefficient (MFCC) for feature extraction. It is trained with 21 male and female speakers in the age group ranging from 20 to 40 years. The system obtained a word recognition accuracy of 87.4% and a sentence recognition accuracy of 84%, when tested with a set of continuous speech data.
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A connected digit speech recognition is important in many applications such as automated banking system, catalogue-dialing, automatic data entry, automated banking system, etc. This paper presents an optimum speaker-independent connected digit recognizer forMalayalam language. The system employs Perceptual Linear Predictive (PLP) cepstral coefficient for speech parameterization and continuous density Hidden Markov Model (HMM) in the recognition process. Viterbi algorithm is used for decoding. The training data base has the utterance of 21 speakers from the age group of 20 to 40 years and the sound is recorded in the normal office environment where each speaker is asked to read 20 set of continuous digits. The system obtained an accuracy of 99.5 % with the unseen data.
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When simulation modeling is used for performance improvement studies of complex systems such as transport terminals, domain specific conceptual modeling constructs could be used by modelers to create structured models. A two stage procedure which includes identification of the problem characteristics/cluster - ‘knowledge acquisition’ and identification of standard models for the problem cluster – ‘model abstraction’ was found to be effective in creating structured models when applied to certain logistic terminal systems. In this paper we discuss some methods and examples related the knowledge acquisition and model abstraction stages for the development of three different types of model categories of terminal systems
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This paper presents an experimental Receptive-Expressive Multi-Modal Learning Program of Patterned Language Practice for hearing-impaired children.
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Background: Autism spectrum disorders (ASD) and specific language impairment (SLI) are common developmental disorders characterised by deficits in language and communication. The nature of the relationship between them continues to be a matter of debate. This study investigates whether the co-occurrence of ASD and language impairment is associated with differences in severity or pattern of autistic symptomatology or language profile. Methods: Participants (N = 97) were drawn from a total population cohort of 56,946 screened as part of study to ascertain the prevalence of ASD, aged 9 to 14 years. All children received an ICD-10 clinical diagnosis of ASD or No ASD. Children with nonverbal IQ 80 were divided into those with a language impairment (language score of 77 or less) and those without, creating three groups: children with ASD and a language impairment (ALI; N = 41), those with ASD and but no language impairment (ANL; N = 31) and those with language impairment but no ASD (SLI; N = 25). Results: Children with ALI did not show more current autistic symptoms than those with ANL. Children with SLI were well below the threshold for ASD. Their social adaptation was higher than the ASD groups, but still nearly 2 SD below average. In ALI the combination of ASD and language impairment was associated with weaker functional communication and more severe receptive language difficulties than those found in SLI. Receptive and expressive language were equally impaired in ALI, whereas in SLI receptive language was stronger than expressive. Conclusions: Co-occurrence of ASD and language impairment is not associated with increased current autistic symptomatology but appears to be associated with greater impairment in receptive language and functional communication.