Semantic context and visual feature effects in object naming : an fMRI study using arterial spin labeling

Previous behavioral studies reported a robust effect of increased naming latencies when objects to be named were blocked within semantic category, compared to items blocked between category. This semantic context effect has been attributed to various mechanisms including inhibition or excitation of lexico-semantic representations and incremental learning of associations between semantic features and names, and is hypothesized to increase demands on verbal self-monitoring during speech production. Objects within categories also share many visual structural features, introducing a potential confound when interpreting the level at which the context effect might occur. Consistent with previous findings, we report a significant increase in response latencies when naming categorically related objects within blocks, an effect associated with increased perfusion fMRI signal bilaterally in the hippocampus and in the left middle to posterior superior temporal cortex. No perfusion changes were observed in the middle section of the left middle temporal cortex, a region associated with retrieval of lexical-semantic information in previous object naming studies. Although a manipulation of visual feature similarity did not influence naming latencies, we observed perfusion increases in the perirhinal cortex for naming objects with similar visual features that interacted with the semantic context in which objects were named. These results provide support for the view that the semantic context effect in object naming occurs due to an incremental learning mechanism, and involves increased demands on verbal self-monitoring.

The influence of colour and sound on neuronal activation during visual object naming

This paper investigates how neuronal activation for naming photographs of objects is influenced by the addition of appropriate colour or sound. Behaviourally, both colour and sound are known to facilitate object recognition from visual form. However, previous functional imaging studies have shown inconsistent effects. For example, the addition of appropriate colour has been shown to reduce antero-medial temporal activation whereas the addition of sound has been shown to increase posterior superior temporal activation. Here we compared the effect of adding colour or sound cues in the same experiment. We found that the addition of either the appropriate colour or sound increased activation for naming photographs of objects in bilateral occipital regions and the right anterior fusiform. Moreover, the addition of colour reduced left antero-medial temporal activation but this effect was not observed for the addition of object sound. We propose that activation in bilateral occipital and right fusiform areas precedes the integration of visual form with either its colour or associated sound. In contrast, left antero-medial temporal activation is reduced because object recognition is facilitated after colour and form have been integrated.

Integrating visual and tactile information in the perirhinal cortex

By virtue of its widespread afferent projections, perirhinal cortex is thought to bind polymodal information into abstract object-level representations. Consistent with this proposal, deficits in cross-modal integration have been reported after perirhinal lesions in nonhuman primates. It is therefore surprising that imaging studies of humans have not observed perirhinal activation during visual-tactile object matching. Critically, however, these studies did not differentiate between congruent and incongruent trials. This is important because successful integration can only occur when polymodal information indicates a single object (congruent) rather than different objects (incongruent). We scanned neurologically intact individuals using functional magnetic resonance imaging (fMRI) while they matched shapes. We found higher perirhinal activation bilaterally for cross-modal (visual-tactile) than unimodal (visual-visual or tactile-tactile) matching, but only when visual and tactile attributes were congruent. Our results demonstrate that the human perirhinal cortex is involved in cross-modal, visual-tactile, integration and, thus, indicate a functional homology between human and monkey perirhinal cortices.

The effect of prior visual information on recognition of speech and sounds

To identify and categorize complex stimuli such as familiar objects or speech, the human brain integrates information that is abstracted at multiple levels from its sensory inputs. Using cross-modal priming for spoken words and sounds, this functional magnetic resonance imaging study identified 3 distinct classes of visuoauditory incongruency effects: visuoauditory incongruency effects were selective for 1) spoken words in the left superior temporal sulcus (STS), 2) environmental sounds in the left angular gyrus (AG), and 3) both words and sounds in the lateral and medial prefrontal cortices (IFS/mPFC). From a cognitive perspective, these incongruency effects suggest that prior visual information influences the neural processes underlying speech and sound recognition at multiple levels, with the STS being involved in phonological, AG in semantic, and mPFC/IFS in higher conceptual processing. In terms of neural mechanisms, effective connectivity analyses (dynamic causal modeling) suggest that these incongruency effects may emerge via greater bottom-up effects from early auditory regions to intermediate multisensory integration areas (i.e., STS and AG). This is consistent with a predictive coding perspective on hierarchical Bayesian inference in the cortex where the domain of the prediction error (phonological vs. semantic) determines its regional expression (middle temporal gyrus/STS vs. AG/intraparietal sulcus).

Threshold MACs

The power of sharing computation in a cryptosystem is crucial in several real-life applications of cryptography. Cryptographic primitives and tasks to which threshold cryptosystems have been applied include variants of digital signature, identification, public-key encryption and block ciphers etc. It is desirable to extend the domain of cryptographic primitives which threshold cryptography can be applied to. This paper studies threshold message authentication codes (threshold MACs). Threshold cryptosystems usually use algebraically homomorphic properties of the underlying cryptographic primitives. A typical approach to construct a threshold cryptographic scheme is to combine a (linear) secret sharing scheme with an algebraically homomorphic cryptographic primitive. The lack of algebraic properties of MACs rules out such an approach to share MACs. In this paper, we propose a method of obtaining a threshold MAC using a combinatorial approach. Our method is generic in the sense that it is applicable to any secure conventional MAC by making use of certain combinatorial objects, such as cover-free families and their variants. We discuss the issues of anonymity in threshold cryptography, a subject that has not been addressed previously in the literature in the field, and we show that there are trade-offis between the anonymity and efficiency of threshold MACs.

Decision strategies for automated visual collision avoidance

This paper provides a preliminary analysis of an autonomous uncooperative collision avoidance strategy for unmanned aircraft using image-based visual control. Assuming target detection, the approach consists of three parts. First, a novel decision strategy is used to determine appropriate reference image features to track for safe avoidance. This is achieved by considering the current rules of the air (regulations), the properties of spiral motion and the expected visual tracking errors. Second, a spherical visual predictive control (VPC) scheme is used to guide the aircraft along a safe spiral-like trajectory about the object. Lastly, a stopping decision based on thresholding a cost function is used to determine when to stop the avoidance behaviour. The approach does not require estimation of range or time to collision, and instead relies on tuning two mutually exclusive decision thresholds to ensure satisfactory performance.

Close-quarters Quadrotor flying for a pole inspection with position based visual servoing and high-speed vision

This paper presents a 100 Hz monocular position based visual servoing system to control a quadrotor flying in close proximity to vertical structures approximating a narrow, locally linear shape. Assuming the object boundaries are represented by parallel vertical lines in the image, detection and tracking is achieved using Plücker line representation and a line tracker. The visual information is fused with IMU data in an EKF framework to provide fast and accurate state estimation. A nested control design provides position and velocity control with respect to the object. Our approach is aimed at high performance on-board control for applications allowing only small error margins and without a motion capture system, as required for real world infrastructure inspection. Simulated and ground-truthed experimental results are presented.

Unbalance identification in large steam turbo-generator unit using a model-based method

Fault identification in industrial machine is a topic of major importance under engineering point of view. In fact, the possibility to identify not only the type, but also the severity and the position of a fault occurred along a shaft-line allows quick maintenance and shorten the downtime. This is really important in the power generation industry where the units are often of several tenths of meters long and where the rotors are enclosed by heavy and pressure-sealed casings. In this paper, an industrial experimental case is presented related to the identification of the unbalance on a large size steam turbine of about 1.3 GW, belonging to a nuclear power plant. The case history is analyzed by considering the vibrations measured by the condition monitoring system of the unit. A model-based method in the frequency domain, developed by the authors, is introduced in detail and it is then used to identify the position of the fault and its severity along the shaft-line. The complete model of the unit (rotor – modeled by means of finite elements, bearings – modeled by linearized damping and stiffness coefficients and foundation – modeled by means of pedestals) is analyzed and discussed before being used for the fault identification. The assessment of the actual fault was done by inspection during a scheduled maintenance and excellent correspondence was found with the identified one by means of authors’ proposed method. Finally a complete discussion is presented about the effectiveness of the method, even in presence of a not fine tuned machine model and considering only few measuring planes for the machine vibration.

Spectroscopic vibrations of austinite (CaZnAsO4⋅OH) and its mineral structure : Implications for identification of secondary arsenic-containing mineral

Austinite (CaZnAsO4⋅OH) is a unique secondary mineral in arsenic-contaminated mine wastes. The infrared and Raman spectroscopies were used to characterize the austenite vibrations. The IR bands at 369, 790 and 416 cm−1 are assigned to the ν2, ν3 and ν4 vibrations of AsO43− unit, respectively. The Raman bands at 814, 779 and 403 cm−1 correspond to the ν1, ν3 and ν4 vibrations of AsO43− unit respectively. The sharp bands at 3265 cm−1 for IR and 3270 cm−1 both reveals that the structural hydroxyl units exist in the austenite structure. The IR and Raman spectra both show that some SO4 units isomorphically replace AsO4 in austinite. X-ray single crystal diffraction provides the arrangement of each atom in the mineral structure, and also confirms that the conclusions made from the vibrational spectra. Micro-powder diffraction was used to confirm our mineral identification due to the small quantity of the austenite crystals.

A hierarchical model of goal directed navigation selects trajectories in a visual environment

We have developed a Hierarchical Look-Ahead Trajectory Model (HiLAM) that incorporates the firing pattern of medial entorhinal grid cells in a planning circuit that includes interactions with hippocampus and prefrontal cortex. We show the model’s flexibility in representing large real world environments using odometry information obtained from challenging video sequences. We acquire the visual data from a camera mounted on a small tele-operated vehicle. The camera has a panoramic field of view with its focal point approximately 5 cm above the ground level, similar to what would be expected from a rat’s point of view. Using established algorithms for calculating perceptual speed from the apparent rate of visual change over time, we generate raw dead reckoning information which loses spatial fidelity over time due to error accumulation. We rectify the loss of fidelity by exploiting the loop-closure detection ability of a biologically inspired, robot navigation model termed RatSLAM. The rectified motion information serves as a velocity input to the HiLAM to encode the environment in the form of grid cell and place cell maps. Finally, we show goal directed path planning results of HiLAM in two different environments, an indoor square maze used in rodent experiments and an outdoor arena more than two orders of magnitude larger than the indoor maze. Together these results bridge for the first time the gap between higher fidelity bio-inspired navigation models (HiLAM) and more abstracted but highly functional bio-inspired robotic mapping systems (RatSLAM), and move from simulated environments into real-world studies in rodent-sized arenas and beyond.

Visual arts learning with iPads

In this chapter Knight & Dooley discuss arts learning and issues of educational authenticity via children’s engagement with iPads (O’Mara & Laidlaw 2011; Shifflet, Toledo & Mattoon 2012). The chapter begins by considering common perceptions about art and how these popular beliefs and conditions affect and influence how children’s art is defined and valorized. The art produced by children using iPads is then discussed through key observations and reflections, and the chapter concludes with some recommendations when selecting apps for making art.

A gray-box neural network-based model identification and fault estimation scheme for nonlinear dynamic systems

A novel gray-box neural network model (GBNNM), including multi-layer perception (MLP) neural network (NN) and integrators, is proposed for a model identification and fault estimation (MIFE) scheme. With the GBNNM, both the nonlinearity and dynamics of a class of nonlinear dynamic systems can be approximated. Unlike previous NN-based model identification methods, the GBNNM directly inherits system dynamics and separately models system nonlinearities. This model corresponds well with the object system and is easy to build. The GBNNM is embedded online as a normal model reference to obtain the quantitative residual between the object system output and the GBNNM output. This residual can accurately indicate the fault offset value, so it is suitable for differing fault severities. To further estimate the fault parameters (FPs), an improved extended state observer (ESO) using the same NNs (IESONN) from the GBNNM is proposed to avoid requiring the knowledge of ESO nonlinearity. Then, the proposed MIFE scheme is applied for reaction wheels (RW) in a satellite attitude control system (SACS). The scheme using the GBNNM is compared with other NNs in the same fault scenario, and several partial loss of effect (LOE) faults with different severities are considered to validate the effectiveness of the FP estimation and its superiority.

On-road rapid identification of high-polluting transport buses

Exhaust emissions from motor vehicles vary widely and depend on factors such as engine operating conditions, fuel, age, mileage and service history. A method has been devised to rapidly identify high-polluting vehicles as they travel on the road. The method is able to monitor emissions from a large number of vehicles in a short time and avoids the need to conduct expensive and time consuming tests on chassis dynamometers. A sample of the exhaust plume is captured as each vehicle passes a roadside monitoring station and the pollutant emission factors are calculated from the measured concentrations using carbon dioxide as a tracer. Although, similar methods have been used to monitor soot and gaseous mass emissions, to-date it has not been used to monitor particle number emissions from a large fleet of vehicles. This is particularly important as epidemiological studies have shown that particle number concentration is an important parameter in determining adverse health effects. The method was applied to measurements of particle number emissions from individual buses in the Brisbane City Council diesel fleet operating on the South-East Busway. Results indicate that the particle number emission factors are gamma- distributed, with a high proportion of the emissions being emitted by a small percentage of the buses. Although most of the high-emitters are the oldest buses in the fleet, there are clear exceptions, with some newer buses emitting as much. We attribute this to their recent service history, particularly pertaining to improper tuning of the engines. We recommend that a targeted correction program would be a highly effective measure in mitigating urban environmental pollution.

Identification of optimal epitopes for Plasmodium falciparum rapid diagnostic tests that target histidine-rich proteins 2 and 3

Rapid diagnostic tests (RDTs) represent important tools to diagnose malaria infection. To improve understanding of the variable performance of RDTs that detect the major target in Plasmodium falciparum, namely, histidine-rich protein 2 (HRP2), and to inform the design of better tests, we undertook detailed mapping of the epitopes recognized by eight HRP-specific monoclonal antibodies (MAbs). To investigate the geographic skewing of this polymorphic protein, we analyzed the distribution of these epitopes in parasites from geographically diverse areas. To identify an ideal amino acid motif for a MAb to target in HRP2 and in the related protein HRP3, we used a purpose-designed script to perform bioinformatic analysis of 448 distinct gene sequences from pfhrp2 and from 99 sequences from the closely related gene pfhrp3. The frequency and distribution of these motifs were also compared to the MAb epitopes. Heat stability testing of MAbs immobilized on nitrocellulose membranes was also performed. Results of these experiments enabled the identification of MAbs with the most desirable characteristics for inclusion in RDTs, including copy number and coverage of target epitopes, geographic skewing, heat stability, and match with the most abundant amino acid motifs identified. This study therefore informs the selection of MAbs to include in malaria RDTs as well as in the generation of improved MAbs that should improve the performance of HRP-detecting malaria RDTs.

Domain-specific application analysis for customized instruction identification

With the increasing importance of Application Domain Specific Processor (ADSP) design, a significant challenge is to identify special-purpose operations for implementation as a customized instruction. While many methodologies have been proposed for this purpose, they all work for a single algorithm chosen from the target application domain. Such algorithm-specific approaches are not suitable for designing instruction sets applicable to a whole family of related algorithms. For an entire range of related algorithms, this paper develops a methodology for identifying compound operations, as a basis for designing “domain-specific” Instruction Set Architectures (ISAs) that can efficiently run most of the algorithms in a given domain. Our methodology combines three different static analysis techniques to identify instruction sequences common to several related algorithms: identification of (non-branching) instruction sequences that occur commonly across the algorithms; identification of instruction sequences nested within iterative constructs that are thus executed frequently; and identification of commonly-occurring instruction sequences that span basic blocks. Choosing different combinations of these results enables us to design domain-specific special operations with different desired characteristics, such as performance or suitability as a library function. To demonstrate our approach, case studies are carried out for a family of thirteen string matching algorithms. Finally, the validity of our static analysis results is confirmed through independent dynamic analysis experiments and performance improvement measurements.