A correlative analysis of CID's grammatical analysis of elicted language with the carrow elicted language inventory

This paper compares the CID GAEL test and the CELI test.

Speech and the hearing-impaired child: evaluation and revision of the CID Speech Skills Worksheet

The purpose of this study was to evaluate the current use of the Central Institute for the Deaf’s Speech Skills Worksheet by teacher of the deaf and speech-language pathologists, review the current literature on speech development in hearing-impaired children, and apply the findings to develop a more comprehensive Speech Skills Worksheet.

An evaluation of the CID perceived self-competence questionnaire

This paper discusses self-esteem and hearing impaired children based on the results of a questionnaire administered to students at CID.

The validation of CID's Grammatical Analysis of Elicited Language with language delayed children

This paper examines the Central Institute for the Deaf’s "Grammatical Analysis of Elicited Language" (GAEL) test of expressive language and whether it identifies children with language disorders. Also examined is the relative difficulty of each of the grammatical categories sampled on the GAEL in relation to the standardization sample.

Evaluation of a feedback equalization algorithm in the CID Wearable Digital Hearing Aid

This paper describes the results of an investigation which examined the efficacy of a feedback equalization algorithm incorporated into the Central Institute for the Deaf Wearable Digital Hearing Aid. The study examined whether the feedback equalization would allow for greater usable gains when subjects listened to soft speech signals, and if so, whether or not this would improve speech intelligibility.

An overview of Meniere's Disease for the CID graduate student

This paper provides an overview of Meniere's Disease.

The effect of the handwriting without tears program on student cursive writing achievement at Central Institute for the Deaf (CID)

Handwriting Without Tears (HWT) is a multi-sensory program that provides a simpler approach to the instruction of cursive handwriting. It was administered to a sample of third graders to assess the effectiveness of the program and determine if it would be a viable option for handwriting instruction at CID.

Caracterização de um grupo formativo numa experiência educacional inclusiva: a escola CID em Porto Alegre/RS

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

CID: an efficient complexity-invariant distance for time series

The ubiquity of time series data across almost all human endeavors has produced a great interest in time series data mining in the last decade. While dozens of classification algorithms have been applied to time series, recent empirical evidence strongly suggests that simple nearest neighbor classification is exceptionally difficult to beat. The choice of distance measure used by the nearest neighbor algorithm is important, and depends on the invariances required by the domain. For example, motion capture data typically requires invariance to warping, and cardiology data requires invariance to the baseline (the mean value). Similarly, recent work suggests that for time series clustering, the choice of clustering algorithm is much less important than the choice of distance measure used.In this work we make a somewhat surprising claim. There is an invariance that the community seems to have missed, complexity invariance. Intuitively, the problem is that in many domains the different classes may have different complexities, and pairs of complex objects, even those which subjectively may seem very similar to the human eye, tend to be further apart under current distance measures than pairs of simple objects. This fact introduces errors in nearest neighbor classification, where some complex objects may be incorrectly assigned to a simpler class. Similarly, for clustering this effect can introduce errors by “suggesting” to the clustering algorithm that subjectively similar, but complex objects belong in a sparser and larger diameter cluster than is truly warranted.We introduce the first complexity-invariant distance measure for time series, and show that it generally produces significant improvements in classification and clustering accuracy. We further show that this improvement does not compromise efficiency, since we can lower bound the measure and use a modification of triangular inequality, thus making use of most existing indexing and data mining algorithms. We evaluate our ideas with the largest and most comprehensive set of time series mining experiments ever attempted in a single work, and show that complexity-invariant distance measures can produce improvements in classification and clustering in the vast majority of cases.

Le Cid : tragédie

par P. Corneille. Mit grammatikalischen Regeln ... bearb. von Georg Kißling ...