Elaborate Task Research Articles

Influence of visual feedback on human task performance in ITER remote handling

In ITER, maintenance operations will be largely performed by remote handling (RH). Before ITER can be put into operation, safety regulations and licensing authorities require proof of maintainability for critical components. Part of the proof will come from using standard components and procedures. Additional verification and validation is based on simulation and hardware tests in 1:1 scale mockups.The Master Slave manipulator system (MS2) Benchmark Product was designed to implement a reference set of maintenance tasks representative for ITER remote handling. Experiments were performed with two versions of the Benchmark Product. In both experiments, the quality of visual feedback varied by exchanging direct view with indirect view (using video cameras) in order to measure and analyze its impact on human task performance.The first experiment showed that both experienced and novice RH operators perform a simple task significantly better with direct visual feedback than with camera feedback. A more complex task showed a large variation in results and could not be completed by many novice operators. Experienced operators commented on both the mechanical design and visual feedback. In a second experiment, a more elaborate task was tested on an improved Benchmark product. Again, the task was performed significantly faster with direct visual feedback than with camera feedback. In post-test interviews, operators indicated that they regarded the lack of 3D perception as the primary factor hindering their performance.

The task of elaboration of screening information system in medical facilities

The medical information technologies are analyzed. The technology of using screening procedures is described. The approach for evaluating the effectiveness of medical facilities is provided

The mediating effect of cognitive development on children's worry elaboration

The present study investigated how developmentally determined cognitive mechanisms, holding theoretical links to the worry process, mediate the relationship between Age and Worry Elaboration in children. Sixty-four children aged 3–7 (M = 5.58, SD = 1.28) were presented with a Conservation of Liquid task assessing their Cognitive Development (specifically Concrete Operational Skills), a false-belief task to measure possession of Belief–Desire Theory of Mind, and a task measuring the ability to acknowledge multiple possibilities. The ability to elaborate on potential negative outcomes was assessed using a Worry Elaboration task. Mediation analysis revealed that all three variables significantly mediated the relationship between Age and Worry Elaboration. A multiple mediation model is presented in which Concrete Operational Skills, Belief–Desire Theory of Mind and Multiple Possibilities understanding mediate the relationship between Age and Worry Elaboration.

Exploratory Analysis of Time-Series with ChronoLenses

Visual representations of time-series are useful for tasks such as identifying trends, patterns and anomalies in the data. Many techniques have been devised to make these visual representations more scalable, enabling the simultaneous display of multiple variables, as well as the multi-scale display of time-series of very high resolution or that span long time periods. There has been comparatively little research on how to support the more elaborate tasks associated with the exploratory visual analysis of timeseries, e.g., visualizing derived values, identifying correlations, or discovering anomalies beyond obvious outliers. Such tasks typically require deriving new time-series from the original data, trying different functions and parameters in an iterative manner. We introduce a novel visualization technique called ChronoLenses, aimed at supporting users in such exploratory tasks. ChronoLenses perform on-the-fly transformation of the data points in their focus area, tightly integrating visual analysis with user actions, and enabling the progressive construction of advanced visual analysis pipelines.

A hierarchical multiple-model approach for detection and isolation of robotic actuator faults

Modern robotic systems perform elaborate tasks in complicated environments and have close interactions with humans. Therefore fault detection and isolation (FDI) schemes must be carefully designed and implemented on robotic systems in order to guarantee safe and reliable operations. In this paper, we propose a hierarchical multiple-model FDI (HMM-FDI) scheme to detect and isolate actuator faults of robot manipulators. The proposed algorithm performs FDI in stages and refines the associated model set at each stage. Consequently only a small number of models are required to detect and isolate various types of unexpected actuator faults, including abrupt faults, incipient faults, and simultaneous faults. In addition, the computational load is alleviated due to the reduced-sized model set. The relation between the fault detection stage of the HMM-FDI scheme and the likelihood ratio test is explicitly revealed and theoretical upper bounds of the false alarm and missed detection probabilities are evaluated. Then we conduct experiments to demonstrate the ability of the HMM-FDI scheme in successful and immediate detection and isolation of actuator faults.

Learning spatial relationships between objects

Although a manipulator must interact with objects in terms of their full complexity, it is the qualitative structure of the objects in an environment and the relationships between them which define the composition of that environment, and allow for the construction of efficient plans to enable the completion of various elaborate tasks. In this paper we present an algorithm which redescribes a scene in terms of a layered representation, from labeled point clouds of the objects in the scene. The representation includes a qualitative description of the structure of the objects, as well as the symbolic relationships between them. This is achieved by constructing contact point networks of the objects, which are topological representations of how each object is used in that particular scene, and are based on the regions of contact between objects. We demonstrate the performance of the algorithm, by presenting results from the algorithm tested on a database of stereo images. This shows a high percentage of correctly classified relationships, as well as the discovery of interesting topological features. This output provides a layered representation of a scene, giving symbolic meaning to the inter-object relationships useful for subsequent commonsense reasoning and decision making.

Compounds In Literature (CIL): screening for compounds and relatives in PubMed

Searching for certain compounds in literature can be an elaborate task, with many compounds having several different synonyms. Often, only the structure is known but not its name. Furthermore, rarely investigated compounds may not be described in the available literature at all. In such cases, preceding searches for described similar compounds facilitate literature mining. Highlighted names of proteins in selected texts may further accelerate the time-consuming process of literary research. Compounds In Literature (CIL) provides a web interface to automatically find names, structures, and similar structures in over 28 million compounds of PubChem and more than 18 million citations provided by the PubMed service. CIL's pre-calculated database contains more than 56 million parent compound-abstract relations. Found compounds, relatives and abstracts are related to proteins in a concise 'heat map'-like overview. Compounds and proteins are highlighted in their respective abstracts, and are provided with links to PubChem and UniProt. An easy-to-use web interface with detailed descriptions, help and statistics is available from http://cil.pharmaceutical-bioinformatics.de. stefan.guenther@pharmazie.uni-freiburg.de.

Effects of semantic elaboration and typicality on picture naming in Alzheimer disease

Purpose Individuals with probable Alzheimer disease (pAD) are frequently impaired at picture naming. This study examined whether a semantic elaboration task would facilitate naming in pAD, and whether training either semantically typical or atypical stimulus items facilitated generalized improvement in picture naming and category generation tasks. Methods Twelve adults with mild-moderate pAD participated in the study. Participants performed an experimental semantic elaboration training task using a subset of typical items from one category and atypical items from another category. The third category, acted as a control (i.e., no items were trained). The study assessed change in category generation and a picture naming within the three target categories. Results Individuals showed significantly improved category generation and naming, but changes were not limited to trained categories. Naming of trained atypical items improved significantly. Participants showed significantly improved naming of untrained typical items from categories trained with typical items. Conclusions Semantic elaboration of typical items within a semantic category can lead to generalized improvement in other typical items in the category in mild-moderate pAD. This is consistent with theories postulating that typical category items share overlapping distributed representations. Further exploration of the effects of semantic elaboration on word-finding in pAD is warranted, especially the possibility of within-category generalization. Learning outcomes: After reading this article, the reader will be able to: (1) explain how word-finding is affected by probable Alzheimer disease; (2) identify ways word finding is usually assessed in Alzheimer's disease; (3) describe the effects of training typical versus atypical items from a category in people with aphasia; and (4) describe the effects of training people with Alzheimer's disease on typical versus atypical items from a category.

Solving future problems: Default network and executive activity associated with goal-directed mental simulations

Mental simulations are often focused on a goal in the future or a problem to be solved. Recent neuroimaging studies have associated mental simulations of the future with default network activity, but the simulations in these studies were not typically directed toward achieving a particular goal. Goal-directed simulation requires cognitive control to maintain information, make decisions, and coordinate abstract action sequences. Therefore, it should recruit not only the default network, but also executive regions. To investigate whether default network and executive regions can be coactive in the context of goal-directed simulation, we designed a problem-solving task in which participants simulated solving several specific problems in imaginary scenarios while in the MRI scanner. We analyzed brain activity during simulation relative to a semantic elaboration task and found that goal-directed simulation engaged core regions of the default network and executive dorsolateral prefrontal cortex. A functional connectivity analysis with posterior cingulate and dorsolateral prefrontal cortex seeds revealed that activity in these regions was coupled throughout the goal-directed simulation period and associated with a distributed network of other default and executive regions, including medial prefrontal cortex, medial temporal, and parietal regions.

A software framework for multimodal interactive simulations (SoFMIS).

The development of a multimodal interactive simulation is a very elaborate task due to the various complex software components involved, which run simultaneously at very high rates with maximum CPU load. In this work, we propose a multimodal parallel simulation framework called SoFMIS to create rapid interactive simulations such as surgical simulations. Our framework offers great flexibility and customization allowing simulation developers and researchers to concentrate on the simulation logic rather than component development.

Emotion processing in the aging brain is modulated by semantic elaboration

The neural correlates of emotion processing have been shown to vary with age: older adults (OAs) exhibit increased frontal activations and, under some circumstances, decreased amygdala activations relative to young adults (YAs) during emotion processing. Some of these differences are additionally modulated by valence, with age-related biases toward positive versus negative stimuli, and are thought to depend on OAs’ capacity for controlled elaboration. However, the role of semantic elaboration in mediating valence effects in the aging brain has not yet been explicitly tested. In the present study, YAs and OAs were scanned while they viewed negative, neutral, and positive pictures during either a deep, elaborative task or a shallow, perceptual task. fMRI results reveal that emotion-related activity in the amygdala is preserved in aging and insensitive to elaboration demands. This study provides novel evidence that differences in valence processing are modulated by elaboration: relative to YAs, OAs show enhanced activity in the medial prefrontal cortex (PFC) and ventrolateral PFC in response to positive versus negative stimuli, but only during elaborative processing. These positive valence effects are predicted by individual differences in executive function in OAs for the deep but not shallow task. Finally, psychophysiological interaction analyses reveal age effects on valence-dependent functional connectivity between medial PFC and ventral striatum, as well as age and task effects on medial PFC-retrosplenial cortex interactions. Altogether, these findings provide support for the hypothesis that valence shifts in the aging brain are mediated by controlled processes such as semantic elaboration, self-referential processing, and emotion regulation.

Mortality and knockdown effects of imidacloprid and methomyl in house fly (Musca domestica L., Diptera: Muscidae) populations

Mortality and knockdown effects of imidacloprid and methomyl in house fly (Musca domestica L., Diptera: Muscidae) populations

Universal merger histories of dark-matter haloes

We study merger histories of dark-matter haloes in a suite of N-body simulations that span different cosmological models. The simulated cases include the up-to-date WMAP5 cosmology and other test cases based on the Einstein-deSitter cosmology with different power spectra. We provide a robust fitting function for the conditional mass function (CMF) of progenitor haloes of a given halo. This fit is valid for the different cosmological models and for different halo masses and redshifts, and it is a significant improvement over earlier estimates. Based on this fit, we develop a simple and accurate technique for transforming the merger history of a given simulated halo into haloes of different mass, redshift and cosmology. Other statistics such as main-progenitor history and merger rates are accurately transformed as well. This method can serve as a useful tool for studying galaxy formation. It is less sensitive to the low accuracy of the fit at small time-steps, and it can thus replace the more elaborate task of construction Monte-Carlo realizations. As an alternative approach, we confirm the earlier finding by Neistein & Dekel that the main-progenitor follows a log-normal distribution. This property of merger trees allows us to better capture their behaviour as a function of time and descendant mass, but a broader suite of simulations is required for evaluating the dependence of the log-normal parameters on the cosmological model.

High field fMRI reveals thalamocortical integration of segregated cognitive and emotional processing in mediodorsal and intralaminar thalamic nuclei

Thalamocortical loops, connecting functionally segregated, higher order cortical regions, and basal ganglia, have been proposed not only for well described motor and sensory regions, but also for limbic and prefrontal areas relevant for affective and cognitive processes. These functions are, however, more specific to humans, rendering most invasive neuroanatomical approaches impossible and interspecies translations difficult. In contrast, non-invasive imaging of functional neuroanatomy using fMRI allows for the development of elaborate task paradigms capable of testing the specific functionalities proposed for these circuits. Until recently, spatial resolution largely limited the anatomical definition of functional clusters at the level of distinct thalamic nuclei. Since their anatomical distinction seems crucial not only for the segregation of cognitive and limbic loops but also for the detection of their functional interaction during cognitive–emotional integration, we applied high resolution fMRI on 7 Tesla. Using an event-related design, we could isolate thalamic effects for preceding attention as well as experience of erotic stimuli. We could demonstrate specific thalamic effects of general emotional arousal in mediodorsal nucleus and effects specific to preceding attention and expectancy in intralaminar centromedian/parafascicular complex. These thalamic effects were paralleled by specific coactivations in the head of caudate nucleus as well as segregated portions of rostral or caudal cingulate cortex and anterior insula supporting distinct thalamo–striato–cortical loops. In addition to predescribed effects of sexual arousal in hypothalamus and ventral striatum, high resolution fMRI could extent this network to paraventricular thalamus encompassing laterodorsal and parataenial nuclei. We could lend evidence to segregated subcortical loops which integrate cognitive and emotional aspects of basic human behavior such as sexual processing.

DNP을 이용한 플랜트의 강인 안정화 기법

본 논문에서는 외란이나 시스템의 파라미터 변동 및 불확실성 등이 존재하는 자동화 설비시스템을 강인하고 정밀하게 제어할 수 있도록 하기 위해 동적 신경망 처리기(DNP)인 신경망 제어기를 설계하였다. 자동화 설비시스템에서 부품의 조립, 가공 등 복잡하고 정교한 임무를 수행시키기 위해서는 end-effector의 이동경로 궤적에 대한 추적제어 뿐만 아니라 목표물에 대하여 접촉하는 힘의 궤적에 대한 추적 제어가 필수적이다. 또한 자동화 설비시스템에서 플랜트의 역기구학적인 좌표변환을 계산하기 위한 학습구조를 개발하였으며, DNP가 이용될 수 있는 예를 설명하였다. 제안된 동적 신경망인 DNP의 구조와 학습 알고리즘을 제시하고 컴퓨터 모의실험을 통해 학습 성능을 증명하였다. In this paper, to bring under robust and accurate control of auto-equipment systems which disturbance, parameter alteration of system, uncertainty and so forth exist, neural network controller called dynamic neural processor(DNP) is designed In order to perform a elaborate task like as assembly, manufacturing and so forth of components, tracking control on the trajectory of power coming in contact with a target as well as tracking control on the movement course trajectory of end-effector is indispensable. Also, the learning architecture to compute inverse kinematic coordinates transformations in the Plants of auto-equipment systems is developed and the example that DNP can be used is explained. The architecture and learning algorithm of the proposed dynamic neural network, the DNP, are described and computer simulations are provided to demonstrate the effectiveness of the proposed learning method using the DNP.

想起エピソードの重要度と鮮明度が気分一致符号化に及ぼす影響―自伝的精緻化課題を用いた検討―

This study investigated mood congruent encoding effects using an autobiographical elaboration task in naturally occurring mood states. We investigated the importance and vividness of the recalled episodes related to whether the stimuli words influenced mood congruent encoding effects. The result of Experiment 1 showed that mood congruent encoding effects occurred when participants in the positive and negative mood conditions recalled high importance episodes. The result of Experiment 2 showed that mood congruent encoding effects occurred when participants in the positive mood condition recalled high vividness episodes and participants in the negative mood condition recalled middle and high vividness episode. The pattern of mood congruent encoding effects differed with the quality of the recalled episodes. These results indicated that the qualities of recalled episodes influenced mood congruent encoding effect.

4SCan/vADME: intelligent library screening as a shortcut from hits to lead compounds

Managing to solve the first step in drug discovery the hit finding can be a quite elaborate task, but it is only the initial step to the final goal; hit-to-lead optimisation still lies ahead and consumes even more time and resources. The solution is rather simple, that is, to take only the most promising compounds into account; but who is going to decide which ones are the most promising among a list of tens of millions of compounds in a virtual combinatorial library? 4SCan/vADME helps by bridging the gap between virtual (combinatorial) libraries designed by chemists and the insilico methods, docking and alignment, for screening databases. After choosing a random starting set, the implemented learning and prediction algorithm iteratively considers only combinations of fragments that have shown to result in more suitable interactions by the chosen method. ADME properties of the final list are then calculated via several insilico methods, resulting in a combined evaluation of the individual compounds target-specific, as well as ADME, properties. Based on the latter list of evaluated compounds, medicinal chemists can then decide which compounds might be the best ones to synthesise first and to serve as possible lead candidates. Following a brief introduction to virtual high-throughput screening techniques, the 4SCan/vADME method is outlined and discussed in this paper, using an example coming out of the 4SC pipeline.

Structural Damage Assessment Using Vibration Modal Analysis

Vibration techniques have been employed for detecting the presence and monitoring the progression of damage in structures. Pinpointing the location of damage is a more complicated and elaborate task. This paper presents modal analysis techniques for locating damage in a wooden wall structure by evaluating damage-sensitive parameters such as resonant pole shifts and mode shapes, residue and stiffness changes. Artificial damage (simulating termite degradation) was created in one of the walls of a specially constructed room. The wall was excited using an impact hammer and its frequency response measured using a laser vibrometer. Resonant poles (plotted in the s-plane) were used for identifying modes that are sensitive to damage, since not all modes are equally affected by the presence of damage. The damaged region was identified by visual comparison of the deformation mode shapes before and after damage. The modal residue and stiffness changes were also quantified for a better representation of the damage location.

Rapid Verification Method for the Trajectory Optimization of Reentry Vehicles

Introduction T HE trajectory optimization of path-constrained nonlinear dynamic systems such as those arising in the guidanceand design of reentry vehicles has long been considereda difŽ cult problem.1i3 Of themany methods to solve such problems, the direct collocation method with sparse nonlinear programming (NLP) has proved to be quite effective. Because direct methods do not tie the resulting solutions to the Pontryaginmaximum principle4 (PMP), a two-step direct–indirect approach has been used successfully for Ž nding extremal solutions.5 One major drawback of the direct–indirect approach is that a signiŽ cant amount of labor is necessary to derive all of the necessary conditions including complex switching and junction conditions for state-constrainedproblems.Even with estimates of the adjoint arcs, solving the multipoint boundary-valueproblem is an elaborate task. Over the past few years, a new approach to solving complex trajectory optimizationproblems has been proposed.6i9 The Legendre pseudospectralmethod is a particularlyeffectivemethod because it providesspectrallyaccuratesolutionsfor the costatesand other covectorswithout the use of any analyticaldifferentialequationsfor the

Analysis of activation in anterior cingulate cortex during cognitive process of selection following somatosensory stimuli: fMRI study with elaborate task paradigms

The anterior cingulate cortex (ACC) has been pointed out to play an important role in the cognitive process of selection underlying “early selection” of perceptually (visually or auditorily) and “late selection” of behaviorally relevant information. However, it is still unclear in cognitive process of selection that the ACC can be activated by somatosensory stimuli as perceptually relevant information. To determine whether the ACC is activated by “early selection” of somatosensory stimuli surely without effects of motor acts as behavior, eighteen normal subjects performed elaborately designed tasks of selection while receiving somatosensory stimuli on their toes of the right and left feet under three different conditions using functional magnetic resonance imaging (fMRI) at 1.5 T. ACC activation was observed to be 2.1 ± 0.3% (mean ± SE) in selection and finger movement as motor acts, and 1.3 ± 0.3% in selection and counting (without motor acts), whereas there was no activation in non-selection. The present fMRI study demonstrates that the ACC is activated by “early selection” following somatosensory stimuli surely without subsequent motor acts.