Low-level Tasks Research Articles

CiteWiz: A Tool for the Visualization of Scientific Citation Networks

We present CiteWiz, an extensible framework for visualization of scientific citation networks. The system is based on a taxonomy of citation database usage for researchers, and provides a timeline visualization for overviews and an influence visualization for detailed views. The timeline displays the general chronology and importance of authors and articles in a citation database, whereas the influence visualization is implemented using the Growing Polygons technique, suitably modified to the context of browsing citation data. Using the latter technique, hierarchies of articles with potentially very long citation chains can be graphically represented. The visualization is augmented with mechanisms for parent–child visualization and suitable interaction techniques for interacting with the view hierarchy and the individual articles in the dataset. We also provide an interactive concept map for keywords and co-authorship using a basic force-directed graph layout scheme. A formal user study indicates that CiteWiz is significantly more efficient than traditional database interfaces for high-level analysis tasks relating to influence and overviews, and equally efficient for low-level tasks such as finding a paper and correlating bibliographical data.

Learning from Observation Paradigm: Leg Task Models for Enabling a Biped Humanoid Robot to Imitate Human Dances

This paper proposes a framework that achieves the Learning from Observation paradigm for learning dance motions. The framework enables a humanoid robot to imitate dance motions captured from human demonstrations. This study especially focuses on leg motions to achieve a novel attempt in which a biped-type robot imitates not only upper body motions but also leg motions including steps. Body differences between the robot and the original dancer make the problem difficult because the differences prevent the robot from straightforwardly following the original motions and they also change dynamic body balance. We propose leg task models, which play a key role in solving the problem. Low-level tasks in leg motion are modelled so that they clearly provide essential information required for keeping dynamic stability and important motion characteristics. The models divide the problem of adapting motions into the problem of recognizing a sequence of the tasks and the problem of executing the task sequence. We have developed a method for recognizing the tasks from captured motion data and a method for generating the motions of the tasks that can be executed by existing robots including HRP-2. HRP-2 successfully performed the generated motions, which imitated a traditional folk dance performed by human dancers.

Pattern Generalization with Graphs and Words: A Cross-Sectional and Longitudinal Analysis of Middle School Students' Representational Fluency

Cross-sectional and longitudinal data from students as they advance through the middle school years (grades 6–8) reveal insights into the development of students' pattern generalization abilities. As expected, students show a preference for lower-level tasks such as reading the data, over more distant predictions and generation of abstractions. Performance data also indicate a verbal advantage that shows greater success when working with words than graphs, a replication of earlier findings comparing words to symbolic equations. Surprisingly, students show a marked advantage with patterns presented in a continuous format (line graphs and verbal rules) as compared to those presented as collections of discrete instances (point-wise graphs and lists of exemplars). Student pattern–generalization performance also was higher when words and graphs were combined. Analyses of student performance patterns and strategy use contribute to an emerging developmental model of representational fluency. The model contributes to research on the development of representational fluency and can inform instructional practices and curriculum design in the area of algebraic development. Results also underscore the impact that perceptual aspects of representations have on students' reasoning, as suggested by an Embodied Cognition view.

Failures in complex systems

Computers are the pervasive technology of our time. As computers become critically tied to human life, it also becomes more important that interactions with them are under control. They are no longer a novelty, but are integrated into the fabric of our world, performing both high and low-level tasks. That is, computers may be used to eliminate heavy, redundant work and more sophisticated machines have been deployed to perform remote surgery or detect subterranean landmines in repopulated civilian areas. The increasing importance of computers in our lives means that it is essential that the design of computer systems incorporates techniques that can ensure reliability, safety, and security. This paper will examine technological mishaps involving the use of computers. This review will include notorious software bugs that have affected finance, communication, transit, defense, health and medicine and other systems or industries. The sequences and etiology of these "accidents" will be discussed as well as how catastrophes may be avoided in the future through lessons and practices based on artificial intelligence research.

Computational Statistics and Data Visualization

This book is the third volume of the Handbook of Computational Statistics and covers the field of Data Visualization. In line with the companion volumes, it contains a collection of chapters by experts in the field to present readers with an up-to-date and comprehensive overview of the state of the art. Data Visualization is an active area of application and research and this is a good time to gather together a summary of current knowledge. Graphic displays are often very effective at communicating information. They are also very often not effective at communicating information. Two important reasons for this state of affairs are that graphics can be produced with a few clicks of the mouse without any thought, and that the design of graphics is not taken seriously in many scientific textbooks. Some people seem to think that preparing good graphics is just a matter of common sense (in which case their common sense cannot be in good shape) and others believe that preparing graphics is a low-level task, not appropriate for scientific attention. This volume of the Handbook of Computational Statistics takes graphics for Data Visualization seriously.

Adaptive task assignment for multiple mobile robots via swarm intelligence approach

This paper describes an adaptive task assignment method for a team of fully distributed mobile robots with initially identical functionalities in unknown task environments. A hierarchical assignment architecture is established for each individual robot. In the higher hierarchy, we employ a simple self-reinforcement learning model inspired by the behavior of social insects to differentiate the initially identical robots into “specialists” of different task types, resulting in stable and flexible division of labor; on the other hand, in dealing with the cooperation problem of the robots engaged in the same type of task, Ant System algorithm is adopted to organize low-level task assignment. To avoid using a centralized component, a “local blackboard” communication mechanism is utilized for knowledge sharing. The proposed method allows the robot team members to adapt themselves to the unknown dynamic environments, respond flexibly to the environmental perturbations and robustly to the modifications in the team arising from mechanical failure. The effectiveness of the presented method is validated in two different task domains: a cooperative concurrent foraging task and a cooperative collection task.

Operator Performance and Intelligent Aiding in Unmanned Aerial Vehicle Scheduling

Interest is increasing in designing systems for controlling unmanned vehicles that will invert the current many-to-one ratio of operators to UVs. Instead of the lower-level tasks that today's UV teams perform, a single operator would focus on high-level supervisory control. A key challenge in designing such single-operator systems is to minimize periods of excessive workload that arise when critical tasks for several UVs occur simultaneously. So, we need decision support that helps the operator evaluate different action alternatives for managing a multiple-UV mission schedule in real time. Two decision support experiments have attempted to provide operators of unmanned aerial vehicles with multivariate scheduling assistance, with mixed results. Those automated decision support tools that provided more local, as opposed to global, visual recommendations performed better. This result suggests that meta-information displays could saturate operators and reduce performance. This article is part of a special issue on Interacting with Autonomy.

Adaptive video communication for an intelligent distributed system: Tuning sensors parameters for surveillance purposes

Surveillance systems include a large set of techniques for both low level and high level tasks. In particular, in the last decade the research community has witnessed a high proliferation of techniques that span from object detection and tracking to object recognition and event understanding. Although some techniques have been proved to be very effective, those tasks cannot be considered solved. Even less, we can consider concluded the research in the field of the analysis of the activities (event analysis). It is this topic together with the problem of the information sharing among different sensors that represents the core of this work. Here, a system architecture for a video surveillance system with distributed intelligence over multiple processing units and with distributed communication over multiple heterogeneous channels (wireless, satellite, local IP networks, etc.) is proposed. A new real-time technique for changing the video transmission parameters (e.g., frame rate, spatial/colour resolution, etc.) according to the available bandwidth (which depends on the number of the detected alarm situations, on the required video quality, etc.) will be presented.

Preserved function of the fusiform face area in schizophrenia as revealed by fMRI

Many lines of evidence suggest that individuals with schizophrenia suffer from face processing deficits. However, the specificity of these deficits and the neural dysfunction underlying them remain unclear. To address these questions, we evaluated the functional status of a critical region for face processing, the fusiform face area (FFA), in subjects with schizophrenia. Fourteen schizophrenia patients and 10 healthy control subjects participated in an fMRI experiment to determine the functional status of the FFA by viewing a series of faces and exemplars of other object categories, while completing a low-level task designed to verify their engagement with the stimuli. Behavioral performance and activation of the FFA were equivalent between groups. Thirteen of 14 patients and all control subjects displayed FFA activation. Furthermore, the degree of FFA activation, as measured by FFA volume and magnitude of activity, was similar between groups. The FFA, a critical region in the neural system subserving the perceptual processing of faces, appears to be intact in schizophrenia. These results call into question the presence of a specific face processing deficit in schizophrenia.

Fuzzy Greenhouse Climate Control System based on a Field Programmable Gate Array

Fuzzy control is a practical alternative for the design of a great variety of control applications. It provides an advisable method for the design of non-linear controllers using heuristic information. This article presents the development of a greenhouse intelligent climate control system that uses a fuzzy controller, based on a field programmable gate array (FPGA). The FPGA has a great potential for use in agricultural technology development due to its characteristics to produce fast prototypes of complex hardware designs with an effective production cost. A low-cost intelligent system designed in a single chip with the task to carry out the complete functionality for the greenhouse climate control was developed. The system proposed here is a good option to unload the low-level tasks (monitoring of climate variables and operation of actuators, such as heaters and windows to control the greenhouse inside temperature) from the main control system, in order to leave to the main controller the high-level tasks as plant monitoring, control of vegetative development, production planning, irrigation system control, which need a high computational power. The system developed in this work consists of: a signal conditioning sub-system, a data-acquisition sub-system, digital/analogue conversion sub-system and a FPGA sub-system. The FPGA sub-system has three units: the synchronisation unit, the personal computer interface unit and the fuzzy logic unit, all implemented within a FPGA-integrated circuit, conforming to a system-on-a-chip (SoC). The design, compilation and simulation of the FPGA sub-system were carried out in the Active-HDL environment using the hardware description language VHDL. The Co-simulation Active-HDL/Simulink and experiments that show the performance of the complete system are presented.

Interoperability with C in Fortran 2003

One of the major new features in the Fortran 2003 is features for interoperability with C © Interop). The intrinsic module ISO_C_BINDING provides:• constants, mostly type parameters, C_NULL_CHAR, C_NULL_PTR, and others,• types, and in particular, TYPE(C_PTR) and TYPE(C_FUNPTR),• procedures, such as C_LOC, C_FUNLOC, C_F_POINTER, C_F_PROCPOINTER and C_ASSOCIATED.A Fortran interface can be specified for a C function with external linkage and used to invoke such a function. The interface has the characteristic BIND(C) label, and must also satisfy some additional restrictions.C Interop can be used to portably use multi-language codes in Fortran. Since most languages interoperate with C, the feature can actually be used to interoperate with other programming languages as well. C Interop can also be used to give access to Fortran programmers to the many standard libraries with widely-used and implemented C interfaces. This includes lower-level tasks such as interfacing with the OS on UNIX-based systems, or using special libraries like OpenGL.For simple API's, developing Fortran interfaces is practically trivial once one gets some experience. For more complicated API's whose full functionality/power is not needed, such as for example TCP/IP sockets or shared-memory segments on UNIX systems, it is often easier to develop a condensed C API/library that does the actual work, and is simpler to interface to from Fortran. However, for libraries like OpenGL, one should provide a full Fortran interface so that the whole API can be accessed. Doing this manually is not easy and is also error-prone due to the size of the OpenGL/GLU/GLUT interfaces. For certain libraries like MPI, a special Fortran interface may be defined for the purposes of efficiency, portability, ease-of-use, or to accommodate for language semantic differences.In this first paper, we will show how to develop a Fortran interface for a simple C API/library. In a second paper, we consider automating the process so that large and more complex API's, and in particular, OpenGL, can be handled. The source codes can be obtained at http://atom.princeton.edu/donev/F2x.Along the way, we identify some problems with the design of C Interop in Fortran 2003.

Separate attentional resources for vision and audition

Current models of attention, typically claim that vision and audition are limited by a common attentional resource which means that visual performance should be adversely affected by a concurrent auditory task and vice versa. Here, we test this implication by measuring auditory (pitch) and visual (contrast) thresholds in conjunction with cross-modal secondary tasks and find that no such interference occurs. Visual contrast discrimination thresholds were unaffected by a concurrent chord or pitch discrimination, and pitch-discrimination thresholds were virtually unaffected by a concurrent visual search or contrast discrimination task. However, if the dual tasks were presented within the same modality, thresholds were raised by a factor of between two (for visual discrimination) and four (for auditory discrimination). These results suggest that at least for low-level tasks such as discriminations of pitch and contrast, each sensory modality is under separate attentional control, rather than being limited by a supramodal attentional resource. This has implications for current theories of attention as well as for the use of multi-sensory media for efficient informational transmission.

Test system design for Hardware-in-Loop evaluation of PEM fuel cells and auxiliaries

In order to evaluate the dynamic behavior of proton exchange membrane (PEM) fuel cells and their auxiliaries, the dynamic capability of the test system must exceed the dynamics of the fastest component within the fuel cell or auxiliary component under test. This criterion is even more critical when a simulated component of the fuel cell system (e.g., the fuel cell stack) is replaced by hardware and Hardware-in-Loop (HiL) methodology is employed. This paper describes the design of a very fast dynamic test system for fuel cell transient research and HiL evaluation. The integration of the real time target (which runs the simulation), the test stand PC (that controls the operation of the test stand), and the programmable logic controller (PLC), for safety and low-level control tasks, into one single integrated unit is successfully completed.

The Effectiveness of Online Task Support vs. Instructor-Led Training

This study investigates the effectiveness of online task support (the wizard type in particular) relative to instructor-led training, and explores the underlying cognitive process in terms of the development of mental models. Ninety-two novice users of Microsoft Access were either trained by an experienced instructor or performed exercises with online task support, and then completed a variety of performance-based tests. Analysis shows that users of online task support tended to outperform instructor-trained individuals on high-level tasks, whereas the performance difference on low-level tasks was not significant. The cognitive processes underlying the difference are also noteworthy. Task support users were more likely to develop conceptual mental models as opposed to procedural ones, which accounted for their better high-level performance. Mental model completeness was also found to be closely associated with performance on both low and high-level tasks. These findings offer support for increased use of online task support.

AN AUTONOMOUS FOREST ROBOT THAT USES A HIERARCHICAL, FUZZY LOGIC CONTROLLER

This article presents a hierarchical fuzzy logic controller that arbitrates recommendations from lower-levelmodules in order to autonomously guide a robot down forest trails. This robot would be used to move logs or trees from wherethey are cut to a location where they could be further processed or loaded onto trucks. The lower-level modules contributerecommendations derived from lower-level tasks or behaviors. Each lower-level module provides its own recommendationbased on its limited perception of the environment. A fuzzy quality measure is used by the hierarchical controller to determinehow best to fuse the individual control recommendations of lower-level modules. The quality measure provides an approximatedetermination of the value of each lower-level module recommendation. These quality measures, as well as other fuzzy setsused in the controller, were defined with a set of parameters. A computer simulation was used to tune subsets of the fuzzy setparameters to improve the performance of the controller. After these parameters were tuned, they were used in the fuzzy logiccontroller, which was tested in a vehicle. The results of these vehicle tests are also discussed in the article.

Implementing distributed control system for intelligent mobile robot

The control system of a mobile robot has a number of issues to deal with in real time, including motion control, mapping, localization, path planning, and sensor processing. Intelligent reasoning, task-oriented behaviors, human-robot interfaces, and communications add more tasks to be solved. This naturally leads to a complex hierarchical control system where various tasks have to be processed concurrently. Many low-level tasks can be handled by a robot’s onboard (host) computer. However, other tasks, such as speech recognition or vision processing, are too computationally intensive for one computer to process. In this case, it is better to consider a distributed design for the control system in networked environments. In order to achieve maximum use of the distributed environment, it is important to design and implement the distributed system and its communication mechanisms in an effective and flexible way. This article describes our approach to designing and implementing a distributed control system for an intelligent mobile robot. We present our implementation of such a distributed control system for a prototype mobile robot. We focus our discussion on the system architecture, distributed communication mechanisms, and distributed robot control.

Motor unit action potential rate and motor unit action potential shape properties in subjects with work-related chronic pain.

The objective of this study was to investigate differences in motor control of the trapezius muscle in cases with work-related chronic pain, compared to healthy controls. Ten cases with chronic pain and 13 controls participated in the study. Electromyographic (EMG) signals were recorded from the upper trapezius during five computer work-related tasks. Motor control was assessed using global root-mean-square value (RMS(G)), motor unit action potential (MUAP) rate (number of MUAPs per second, MR) and two MUAP shape parameters, i.e. root-mean-square (RMS(MUAP)) and median frequency (FMED(MUAP)). MR and FMED(MUAP) were higher for the cases than for the controls (P < 0.05). RMS(MUAP) showed a trend for higher values in the chronic pain group (P < 0.13), whereas RMS(G) did not show a significant difference between the groups. The higher MR, FMED(MUAP) and the trend for higher RMS(MUAP) suggest that more high-threshold MUs contribute to low-level computer work-related tasks in chronic pain cases. Additionally, the results suggest that the input of the central nervous system to the muscle is higher in the cases with chronic pain.

Interaction between High-Level and Low-Level Image Analysis for Semantic Video Object Extraction

The task of extracting a semantic video object is split into two subproblems, namely, object segmentation and region segmentation. Object segmentation relies on a priori assumptions, whereas region segmentation is data-driven and can be solved in an automatic manner. These two subproblems are not mutually independent, and they can benefit from interactions with each other. In this paper, a framework for such interaction is formulated. This representation scheme based on region segmentation and semantic segmentation is compatible with the view that image analysis and scene understanding problems can be decomposed into low-level and high-level tasks. Low-level tasks pertain to region-oriented processing, whereas the high-level tasks are closely related to object-level processing. This approach emulates the human visual system: what one "sees" in a scene depends on the scene itself (region segmentation) as well as on the cognitive task (semantic segmentation) at hand. The higher-level segmentation results in a partition corresponding to semantic video objects. Semantic video objects do not usually have invariant physical properties and the definition depends on the application. Hence, the definition incorporates complex domain-specific knowledge and is not easy to generalize. For the specific implementation used in this paper, motion is used as a clue to semantic information. In this framework, an automatic algorithm is presented for computing the semantic partition based on color change detection. The change detection strategy is designed to be immune to the sensor noise and local illumination variations. The lower-level segmentation identifies the partition corresponding to perceptually uniform regions. These regions are derived by clustering in an -dimensional feature space, composed of static as well as dynamic image attributes. We propose an interaction mechanism between the semantic and the region partitions which allows to cope with multiple simultaneous objects. Experimental results show that the proposed method extracts semantic video objects with high spatial accuracy and temporal coherence.

Human movement capture and analysis in intelligent environments

Investigators from multiple disciplines and applications areas are interested in Human body modeling, tracking, and synthesis related topics. These topics offer fertile ground for challenging research problems aswell as potential for awide range of applications. Our own interest and involvement in human modeling, analysis, and synthesis comes froma very specific need: that of developing “intelligent” environments or spaces [1–3]. An intelligent environment automatically derives and dynamically maintains an awareness of its composition as well as events and activities occurring within.Moreover, these spaces should be responsive to specific events and triggers. Such spaces need not be limited to rooms in buildings, but extend to outdoor environments [4] and any other spaces that humans occupy such as a performance on a stage or an automobile on a highway [5]. The spaces are monitored by multiple audio and video sensors, which can be unobtrusively embedded in the infrastructure. To avoid intrusion on the normal human activities in the space, all sensors, processors, and communication devices should remain “invisible” in the infrastructure. The system should also support natural and flexible interactions among the participants without specialized or encumbering devices. In a conference room environment, multiple video cameras and microphones may be embedded in walls and furniture. Video and audio signals are analyzed in real time for a wide range of low-level tasks, including person identification, localization and tracking, and gesture and voice recognition [6]. Combining the analysis tasks with human face and body synthesis enables efficient interactions with remote observers, effectively merging disjoint spaces into a single intelligent environment. We are currently embedding distributed video networks in rooms, laboratories, museums, and even outdoor public spaces in support of experimental research in this domain. This involves the development of new frameworks, architectures, and algorithms for audio and video processing as well as for the control of various functions associated with proper execution of a transaction within such intelligent spaces. These test beds are also helping to identify novel applications of such

Levels of Control During a Collaborative Carrying Task

Three experiments investigated the effect of implementing low-level aspects of motor control for a collaborative carrying task within a VE interface, leaving participants free to devote their cognitive resources to the higher-level components of the task. In the task, participants collaborated with an autonomous virtual human in an immersive virtual environment (VE) to carry an object along a predefined path. In experiment 1, participants took up to three times longer to perform the task with a conventional VE interface, in which they had to explicitly coordinate their hand and body movements, than with an interface that controlled the low-level tasks of grasping and holding onto the virtual object. Experiments 2 and 3 extended the study to include the task of carrying an object along a path that contained obstacles to movement. By allowing participants' virtual arms to stretch slightly, the interface software was able to take over some aspects of obstacle avoidance (another low-level task), and this led to further significant reductions in the time that participants took to perform the carrying task. Improvements in performance also occurred when participants used a tethered viewpoint to control their movements because they could see their immediate surroundings in the VEs. This latter finding demonstrates the superiority of a tethered view perspective to a conventional, human'seye perspective for this type of task.