Validation of ASHA FACS-Functional Assessment of Communication Skills for Alzheimer Disease Population

This study vas aimed to validate the American Speech-Language-Hearing Association Functional Assessment Of Communication Skills (ASHA FACS) for a Brazilian population. The scale was translated and adapted into Portuguese. Thirty-two patients with mild Alzheimer disease (AD). 25 patients with moderate AD. and 51 elderly without dementia were examined with Mini Mental State Examination, Geriatric Depression Scale. and Alzheimer Disease Assessment Scale-Cognitive subscale (ADAS-cog). The ASHA FACS was answered by their relative/caregiver. The scale`s internal consistency. its inter-examiner and intra-examiner`s reproducibility. and scale`s criterion validity were researched by correlation with ADAS-cog,. The sensitivity and specificity Were also researched. Statistical analyses indicated that the ASHA FACS has excellent internal consistency (Cronbach alpha = 0.955), test-retest reliability (interclass correlation coefficient = 0.995; P < 0.001). and inter-examiners (interclass correlation coefficient = 0.998: P < 0.001). It showed excellent criterion validity when correlated with ADAS-cog,. The ASHA FACS scale showed good sensitivity (75.0%) and specificity (82.4%) values once it is an ecologic and broad evaluation. The ASHA FACS Portuguese version is a valid and reliable instrument to verify communication alterations in AD patients and fills an important gap of efficiency indicators for speech language therapy in our country.

Cross-situational and supervised learning in the emergence of communication

Scenarios for the emergence or bootstrap of a lexicon involve the repeated interaction between at least two agents who must reach a consensus on how to name N objects using H words. Here we consider minimal models of two types of learning algorithms: cross-situational learning, in which the individuals determine the meaning of a word by looking for something in common across all observed uses of that word, and supervised operant conditioning learning, in which there is strong feedback between individuals about the intended meaning of the words. Despite the stark differences between these learning schemes, we show that they yield the same communication accuracy in the limits of large N and H, which coincides with the result of the classical occupancy problem of randomly assigning N objects to H words.

Effect of bandwidth knowledge of results on the learning of a grip force control task

An experiment was conducted to investigate the persistence of the effect of ""bandwidth knowledge of results (KR)"" manipulated during the learning phase of performing a manual force-control task. The experiment consisted of two phases, an acquisition phase with the goal of maintaining 60% maximum force in 30 trials, and a second phase with the objective of maintaining 40% of maximum force in 20 further trials. There were four bandwidths of KR: when performance error exceeded 5, 10, or 15% of the target, and a control group (0% bandwidth). Analysis showed that 5, 10, and 15% bandwidth led to better performance than 0% bandwidth KR at the beginning of the second phase and persisted during the extended trials.

Cross-situational learning of object-word mapping using Neural Modeling Fields

The issue of how children learn the meaning of words is fundamental to developmental psychology. The recent attempts to develop or evolve efficient communication protocols among interacting robots or Virtual agents have brought that issue to a central place in more applied research fields, such as computational linguistics and neural networks, as well. An attractive approach to learning an object-word mapping is the so-called cross-situational learning. This learning scenario is based on the intuitive notion that a learner can determine the meaning of a word by finding something in common across all observed uses of that word. Here we show how the deterministic Neural Modeling Fields (NMF) categorization mechanism can be used by the learner as an efficient algorithm to infer the correct object-word mapping. To achieve that we first reduce the original on-line learning problem to a batch learning problem where the inputs to the NMF mechanism are all possible object-word associations that Could be inferred from the cross-situational learning scenario. Since many of those associations are incorrect, they are considered as clutter or noise and discarded automatically by a clutter detector model included in our NMF implementation. With these two key ingredients - batch learning and clutter detection - the NMF mechanism was capable to infer perfectly the correct object-word mapping. (C) 2009 Elsevier Ltd. All rights reserved.

A novel approach for distributed application scheduling based on prediction of communication events

The evolution of commodity computing lead to the possibility of efficient usage of interconnected machines to solve computationally-intensive tasks, which were previously solvable only by using expensive supercomputers. This, however, required new methods for process scheduling and distribution, considering the network latency, communication cost, heterogeneous environments and distributed computing constraints. An efficient distribution of processes over such environments requires an adequate scheduling strategy, as the cost of inefficient process allocation is unacceptably high. Therefore, a knowledge and prediction of application behavior is essential to perform effective scheduling. In this paper, we overview the evolution of scheduling approaches, focusing on distributed environments. We also evaluate the current approaches for process behavior extraction and prediction, aiming at selecting an adequate technique for online prediction of application execution. Based on this evaluation, we propose a novel model for application behavior prediction, considering chaotic properties of such behavior and the automatic detection of critical execution points. The proposed model is applied and evaluated for process scheduling in cluster and grid computing environments. The obtained results demonstrate that prediction of the process behavior is essential for efficient scheduling in large-scale and heterogeneous distributed environments, outperforming conventional scheduling policies by a factor of 10, and even more in some cases. Furthermore, the proposed approach proves to be efficient for online predictions due to its low computational cost and good precision. (C) 2009 Elsevier B.V. All rights reserved.

Learning of shared attention in sociable robotics

Sociable robots are embodied agents that are part of a heterogeneous society of robots and humans. They Should be able to recognize human beings and each other, and to engage in social, interactions. The use of a robotic architecture may strongly reduce the time and effort required to construct a sociable robot. Such architecture must have structures and mechanisms to allow social interaction. behavior control and learning from environment. Learning processes described oil Science of Behavior Analysis may lead to the development of promising methods and Structures for constructing robots able to behave socially and learn through interactions from the environment by a process of contingency learning. In this paper, we present a robotic architecture inspired from Behavior Analysis. Methods and structures of the proposed architecture, including a hybrid knowledge representation. are presented and discussed. The architecture has been evaluated in the context of a nontrivial real problem: the learning of the shared attention, employing an interactive robotic head. The learning capabilities of this architecture have been analyzed by observing the robot interacting with the human and the environment. The obtained results show that the robotic architecture is able to produce appropriate behavior and to learn from social interaction. (C) 2009 Elsevier Inc. All rights reserved.

LEARNING A COMPLEX MOTOR SKILL FROM VIDEO AND POINT-LIGHT DEMONSTRATIONS

The aim of this Study was to compare the learning process of a highly complex ballet skill following demonstrations of point light and video models 16 participants divided into point light and video groups (ns = 8) performed 160 trials of a pirouette equally distributed in blocks of 20 trials alternating periods of demonstration and practice with a retention test a day later Measures of head and trunk oscillation coordination d1 parity from the model and movement time difference showed similarities between video and point light groups ballet experts evaluations indicated superiority of performance in the video over the point light group Results are discussed in terms of the task requirements of dissociation between head and trunk rotations focusing on the hypothesis of sufficiency and higher relevance of information contained in biological motion models applied to learning of complex motor skills

Remote control of CNC machines using the CyberOPC communication system over public networks

During the last few years, the evolution of fieldbus and computers networks allowed the integration of different communication systems involving both production single cells and production cells, as well as other systems for business intelligence, supervision and control. Several well-adopted communication technologies exist today for public and non-public networks. Since most of the industrial applications are time-critical, the requirements of communication systems for remote control differ from common applications for computer networks accessing the Internet, such as Web, e-mail and file transfer. The solution proposed and outlined in this work is called CyberOPC. It includes the study and the implementation of a new open communication system for remote control of industrial CNC machines, making the transmission delay for time-critical control data shorter than other OPC-based solutions, and fulfilling cyber security requirements.

Assessing deaf and hearing children`s communication in Brazil

In Brazil there are no specific tests for either signed or spoken language for deaf children. A protocol evaluating communicative abilities independent of modality of communication (sign language or spoken language), and comprising assessments of (a) pragmatic profile; (b) modality of communication and linguistic level; (c) complexity of communication; and (d) style and efficacy of communication between parent and child was administered to 127 deaf and hearing children. The children, aged 3-6 years old, were distributed in three groups: 20 with severe hearing loss, 40 with profound hearing loss and 67 normally hearing. Deaf children were found to be delayed, independent of their linguistic level and preferred modality of communication. The protocol in this study proved to be an useful instrument for gathering relevant information about the three groups of preschool children`s communicative abilities, and particularly suitable for use in countries where standardized assessments are not available. Learning outcomes: The reader will be introduced to the use of an assessment protocol comprising its development, application and data analysis. The reader will be informed about assessment of deaf children`s preferred modality of communication, by the participation of a bilingual (sign language user) professional. Communication abilities can be assessed independently of the linguistic modality. In developing countries in general, where simple and easy to administer assessments tools are scarce, such a protocol is of specific value. (c) 2010 Elsevier Inc. All rights reserved.

Endoscopic Anatomy of the Pterygopalatine Fossa and the Transpterygoid Approach: Development of a Surgical Instruction Model

Introduction: The pterygopalatine fossa (PPF) is a narrow space located between the posterior wall of the antrum and the pterygoid plates. Surgical access to the PPF is difficult because of its protected position and its complex neurovascular anatomy. Endonasal approaches using rod lens endoscopes, however, provide better visualization of this area and are associated with less morbidity than external approaches. Our aim was to develop a simple anatomical model using cadaveric specimens injected with intravascular colored silicone to demonstrate the endoscopic anatomy of the PPF. This model could be used for surgical instruction of the transpterygoid approach. Methods: We dissected six PPF in three cadaveric specimens prepared with intravascular injection of colored material using two different injection techniques. An endoscopic endonasal approach, including a wide nasoantral window and removal of the posterior antrum wall, provided access to the PPF. Results: We produced our best anatomical model injecting colored silicone via the common carotid artery. We found that, using an endoscopic approach, a retrograde dissection of the sphenopalatine artery helped to identify the internal maxillary artery (IMA) and its branches. Neural structures were identified deeper to the vascular elements. Notable anatomical landmarks for the endoscopic surgeon are the vidian nerve and its canal that leads to the petrous portion of the internal carotid artery (ICA), and the foramen rotundum, and V2 that leads to Meckel`s cave in the middle cranial fossa. These two nerves, vidian and V2, are separated by a pyramidal shaped bone and its apex marks the ICA. Conclusion: Our anatomical model provides the means to learn the endoscopic anatomy of the PPF and may be used for the simulation of surgical techniques. An endoscopic endonasal approach provides adequate exposure to all anatomical structures within the PPF. These structures may be used as landmarks to identify and control deeper neurovascular structures. The significance is that an anatomical model facilitates learning the surgical anatomy and the acquisition of surgical skills. A dissection superficial to the vascular structures preserves the neural elements. These nerves and their bony foramina, such as the vidian nerve and V2, are critical anatomical landmarks to identify and control the ICA at the skull base.

A game theoretical approach to the evolution of structured communication codes

Structured meaning-signal mappings, i.e., mappings that preserve neighborhood relationships by associating similar signals with similar meanings, are advantageous in an environment where signals are corrupted by noise and sub-optimal meaning inferences are rewarded as well. The evolution of these mappings, however, cannot be explained within a traditional language evolutionary game scenario in which individuals meet randomly because the evolutionary dynamics is trapped in local maxima that do not reflect the structure of the meaning and signal spaces. Here we use a simple game theoretical model to show analytically that when individuals adopting the same communication code meet more frequently than individuals using different codes-a result of the spatial organization of the population-then advantageous linguistic innovations can spread and take over the population. In addition, we report results of simulations in which an individual can communicate only with its K nearest neighbors and show that the probability that the lineage of a mutant that uses a more efficient communication code becomes fixed decreases exponentially with increasing K. These findings support the mother tongue hypothesis that human language evolved as a communication system used among kin, especially between mothers and offspring.