Hypnosis as a Technique for the Treatment of Stuttering

AbstractVarious recorded studies have found that it is possible to reduce the severity of stuttering through the use of hypnosis. Yet, there have been very limited studies on the effect of hypnosis as a means of stuttering treatment. Some studies concluded that hypnosis reduces the severity of stuttering in the long term (Moss & Oackley, 1997), while others claim to a short term effect (Bloodstein, 1995). Most studies do not elaborate on the measures or techniques used to evaluate the impact of hypnosis treatment on stuttering. This study examined the influence of hypnotic therapy on a PWS volunteer. The stammering was analyzed in two ways:1) Measurement of the overt stammering: a. percentage of stammering syllables- ss%, b. Stuttering like dysfluency SLD (Yairi, 1996). c. average number of repetitions (Ambrose & Yairi 1999).2) Measurement of covert stammering was done by: a. Speech Situation Checklist-SSC (Brutten, 1985). b. State Trait Anxiety Inventory (STAI) (Spielberger, 1966).During the hypnosis the participant was offered suggestions of ego strengthening, treating past traumas, and enhancing his sense of control. The treatment took place through 8 treatment sessions and one follow up session. The suggestions were offered to try to reduce the severity of both the overt and covert features of stammering. The stuttering was recorded while reading and spontaneously speaking in the beginning and ending of each session. In addition, two questionnaires were filled in at the beginning and ending of therapy. The results showed that the stammering severity was reduced at the end of each session compared to the beginning. The results also showed that some of the improvements only lasted a short period of time while others lasted until the follow up session. Moreover, the covert features of stammering pointed to a change in the subject's feelings and perceptions

Representation design benchmarks : a design-time aid for VPL navigable static representations

A weakness of many interactive visual programming languages (VPLs) is their static representations. Lack of an adequate static representation places a heavy cognitive burden on a VPL's programmers, because they must remember potentially long dynamic sequences of screen displays in order to understand a previously-written program. However, although this problem is widely acknowledged, research on how to design better static representations for interactive VPLs is still in its infancy. Building upon the cognitive dimensions developed for programming languages by cognitive psychologists Green and others, we have developed a set of concrete benchmarks for VPL designers to use when designing new static representations. These benchmarks provide design-time information that can be used to improve a VPL's static representation

Querying industrial stream-temporal data: An ontology-based visual approach

An increasing number of sensors are being deployed in business-critical environments, systems, and equipment; and stream a vast amount of data. The operational efficiency and effectiveness of business processes rely on domain experts’ agility in interpreting data into actionable business information. A domain expert has extensive domain knowledge but not necessarily skills and knowledge on databases and formal query languages. Therefore, centralised approaches are often preferred. These require IT experts to translate the information needs of domain experts into extract-transform-load (ETL) processes in order to extract and integrate data and then let domain experts apply predefined analytics. Since such a workflow is too time intensive, heavy-weight and inflexible given the high volume and velocity of data, domain experts need to extract and analyse the data of interest directly. Ontologies, i.e., semantically rich conceptual domain models, present an intelligible solution by describing the domain of interest on a higher level of abstraction closer to the reality. Moreover, recent ontology-based data access (OBDA) technologies enable end users to formulate their information needs into queries using a set of terms defined in an ontology. Ontological queries could then be translated into SQL or some other database query languages, and executed over the data in its original place and format automatically. To this end, this article reports an ontology-based visual query system (VQS), namely OptiqueVQS, how it is extended for a stream-temporal query language called STARQL, a user experiment with the domain experts at Siemens AG, and STARQL’s query answering performance over a proof of concept implementation for PostgreSQL

Ontology-based end-user visual query formulation: Why, what, who, how, and which?

Value creation in an organisation is a time-sensitive and data-intensive process, yet it is often delayed and bounded by the reliance on IT experts extracting data for domain experts. Hence, there is a need for providing people who are not professional developers with the flexibility to pose relatively complex and ad hoc queries in an easy and intuitive way. In this respect, visual methods for query formulation undertake the challenge of making querying independent of users’ technical skills and the knowledge of the underlying textual query language and the structure of data. An ontology is more promising than the logical schema of the underlying data for guiding users in formulating queries, since it provides a richer vocabulary closer to the users’ understanding. However, on the one hand, today the most of world’s enterprise data reside in relational databases rather than triple stores, and on the other, visual query formulation has become more compelling due to ever-increasing data size and complexity—known as Big Data. This article presents and argues for ontology-based visual query formulation for end-users; discusses its feasibility in terms of ontology-based data access, which virtualises legacy relational databases as RDF, and the dimensions of Big Data; presents key conceptual aspects and dimensions, challenges, and requirements; and reviews, categorises, and discusses notable approaches and systems