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This paper presents a novel tactile navigation system for the blind. The device is portable and cost effective, and will allow visually impaired individuals to navigate through familiar and non-familiar environments without relying on the assistance of a guide. The “Tactile Handle” consists of an array of vibro-tactile actuators positioned to match the finger phalanxes, proximity sensors, and an embedded micro-controller. The handle processes sensor signals and outputs information to the user through variable and synchronized vibrations, which will enhance the sense of orientation and distance for the user. The prototype has an ergonomic design, is lightweight, compact, and adjustable to different hand sizes. This paper describes the concept of its use as a navigation system for the visually impaired and the preliminary results for the tactile perception of 30 sighted users of different genders and hand sizes.

A growing attention has been paid to the ontology learning domain. This is due to its importance for overcoming the limits of manual ontology building. Thus, ontology evaluation becomes crucial and very much-needed in order to select the best performing ontology learning method. The aim of the present paper is to offer a new method for assessing a learned ontology in comparison to a gold standard one. In order to avoid issues of previous precision and recall measures, the proposed method is based on a new ontology disambiguation engine. The latter provides meaning annotations to concepts. Next, we propose a set of measures that exploits the meanings of concepts to evaluate the learned ontologies. To prove the efficiency of the proposed solution, we conduct a set of experiments that test our method on well-known ontologies. Experiments show that these measures scale gradually in the closed interval of [0; 1] as learned ontologies deviate increasingly from the gold standard.

Purpose – This paper aims to propose a new qualitative indicator for the evaluation of the productions of researchers in any discipline. Design/methodology/approach – Based on the study of existing quantitative indicators, the authors’ approach consisted of the hybridization of two indicators. This hybridization is based on the individual H_index (Hi_index) and H_index contemporary (Hc_index) weighted by qualitative factors. The initial sources of the data are online bibliographic databases, such as Google Scholar and Publish or Perish. Findings – A new scientometric indicator was used to compare the scientific production quality of researchers and their classification (as part of a research community) as the classification of national and international research institutions. The authors have applied a new indicator to compare and classify the members of their laboratory, RIADI, according to their quality of scientific production. Practical implications – The indicator is an improvement of the H_index. It is a measure that can have an impact on society (influencing research attitudes, affecting quality of research). By this contribution, the authors measure more than one aspect by involving all the external factors that can affect the quality of research. Originality/value – This paper fulfils a gap in the literature concerning the absence of a qualitative indicator among the set of existing quantitative measures. Additionally, this paper addresses the limitations of the existing qualitative practices, such as peer review and citation analysis. In the new qualitative indicator, the authors involve all of these qualitative aspects: the influence of the age of the paper, the number of co-authors, the order of the co-authors, the impact factor of journals and the conference rankings.

Topic segmentation is important for many natural language processing applications such as information retrieval, text summarization... In our work, we are interested in the topic segmentation of textual document. We present a survey of related works particularly C99 and TextTiling. Then, we propose an adaptation of these topic segmenters for textual document written in Arabic language named as ArabC99 and ArabTextTiling. For experimental results, we construct an Arabic corpus based on newspapers of different Arab countries. Finally, we evaluate the performance of these new segmenters by comparing them together and to related works using the metrics WindowDiff and F-measure.