Optimal task allocation in hypercube multiprocessor ensembles

Criteria are established to determine the optimal policy for allocating a set of uniform tasks onto a multiprocessor hypercube ensemble. It is shown that the optimal policy depends on the ratio of computation to intertask communication required by the distributed program, and that based on this ratio, tasks should be placed either all on one processor or uniformly distributed over the largest possible hypercube.     

Groupwork and computers: task type and children's performance

Abstract In the majority of British primary schools, children use the computer in groups of two or three. This is partly due to the lack of resources, that is, most classrooms still only have one or two computers to share between around 30 children. Groupwork on computers is also justified for pedagogic reasons. Previous research comparing children working in groups or alone has revealed an advantage for children working in groups although the work undertaken has generally been problem solving tasks. This investigation examined the performance of pairs and individual 6-year old children on a drill and practice program using a pre-test, intervention, post-test design. In comparison to the problem solving evidence, individuals were found to have a significant advantage over pairs during the computer-based task.     

Multiple targets enclosure by robotic swarm

Target enclosure by autonomous robots is useful for many practical applications, for example, surveillance of disaster sites. Scalability is important for autonomous robots because a larger group is more robust against breakdown, accidents, and failure. However, since the traditional models have discussed only the cases in which minimum number of robots enclose a single target, there has been no study on the utilization of the redundant number of robots. In this paper, to achieve a highly scalable target enclosure model about the number of target to enclose, we introduce swarm based task assignment capability to Takayama’s enclosure model. The original model discussed only single target environment but it is well suited for applying to the environments with multiple targets. We show the robots can enclose the targets without predefined position assignment by analytic discussion based on switched systems and a series of computer simulations. As a consequence of this property, the proposed robots can change their target according to the criterion about robot density while they enclose multiple targets.     

Analysing interactive devices based on information resource constraints

Analysis of the usability of an interactive system requires both an understanding of how the system is to be used and a means of assessing the system against that understanding. Such analytic assessments are particularly important in safety-critical systems as latent vulnerabilities may exist which have negative consequences only in certain circumstances. Many existing approaches to assessment use tasks or scenarios to provide explicit representation of their understanding of use. These normative user behaviours have the advantage that they clarify assumptions about how the system will be used but have the disadvantage that they may exclude many plausible deviations from these norms. Assessments of how a design fails to support these user behaviours can be a matter of judgement based on individual experience rather than evidence. We present a systematic formal method for analysing interactive systems that is based on constraints rather than prescribed behaviour. These constraints capture precise assumptions about what information resources are used to perform action. These resources may either reside in the system itself or be external to the system. The approach is applied to two different medical device designs, comparing two infusion pumps currently in common use in hospitals. Comparison of the two devices is based on these resource assumptions to assess consistency of interaction within the design of each device.     

平面设计Photoshop教学的探索与研究

计算机平面设计行业作为知识型的服务产业,在竞争日益激烈的商业社会中发挥着举足轻重的作用。Photoshop(以下简称PS)是一门实践性很强的课程,使用传统的教学方法无法达到满意的教学效果。在教学方法的探索与实践中,采用抛砖引玉引导学习法、案例教学法、情景教学法、先成果后教学法等多种教学方法,引发学生的学习兴趣,培养学生的模仿和创新能力。同时,采用分阶段教学方法,使学生更好地掌握该软件,进一步提高教学质量。     

Discrete particle swarm optimization based on estimation of distribution for terminal assignment problems

Terminal assignment problem (TEAP) is to determine minimum cost links to form a network by connecting a given set of terminals to a given collection of concentrators. This paper presents a novel discrete particle swarm optimization (PSO) based on estimation of distribution (EDA), named DPSO-EDA, for TEAP. EDAs sample new solutions from a probability model which characterizes the distribution of promising solutions in the search space at each generation. The DPSO-EDA incorporates the global statistical information collected from personal best solutions of all particles into the PSO, and therefore each particle has comprehensive learning and search ability. In the DPSO-EDA, a modified constraint handling method based on Hopfield neural network (HNN) is also introduced to fit nicely into the framework of the PSO and thus utilize the merit of the PSO. The DPSO-EDA adopts the asynchronous updating scheme. Further, the DPSO-EDA is applied to a problem directly related to TEAP, the task assignment problem (TAAP), in order to show that the DPSO-EDA can be generalized to other related combinatorial optimization problems. Simulation results on several problem instances show that the DPSO-EDA is better than previous methods.     

Planning and execution through variable resolution planning

Generating sequences of actions–plans–for robots using Automated Planning in stochastic and dynamic environments has been shown to be a difficult task with high computational complexity. These plans are composed of actions whose execution might fail due to different reasons. In many cases, if the execution of an action fails, it prevents the execution of some (or all) of the remainder actions in the plan. Therefore, in most real-world scenarios computing a complete and sound (valid) plan at each (re-)planning step is not worth the computational resources and time required to generate the plan. This is specially true given the high probability of plan execution failure. Besides, in many real-world environments, plans must be generated fast, both at the start of the execution and after every execution failure. In this paper, we present Variable Resolution Planning which uses Automated Planning to quickly compute a reasonable (not necessarily sound) plan. Our approach computes an abstract representation–removing some information from the planning task–which is used once a search depth of $k$ steps has been reached. Thus, our approach generates a plan where the first $k$ actions are applicable if the domain is stationary and deterministic, while the rest of the plan might not be necessarily applicable. The advantages of this approach are that it: is faster than regular full-fledged planning (both in the probabilistic or deterministic settings); does not spend much time on the far future actions that probably will not be executed, since in most cases it will need to replan before executing the end of the plan; and takes into account some information of the far future, as an improvement over pure reactive systems. We present experimental results on different robotics domains that simulate tasks on stochastic environments.     

Distraction 'on the buses': a novel framework of ergonomics methods for identifying sources and effects of bus driver distraction

Driver distraction represents a significant problem in the public transport sector. Various methods exist for investigating distraction; however, the majority are difficult to apply within the context of naturalistic bus driving. This article investigates the nature of bus driver distraction at a major Australian public transport company, including the sources of distraction present, and their effects on driver performance, through the application of a novel framework of ergonomics methods. The framework represents a novel approach for assessing distraction in a real world context. The findings suggest that there are a number of sources of distraction that could potentially distract bus drivers while driving, including those that derive from the driving task itself, and those that derive from the additional requirements associated with bus operation, such as passenger and ticketing-related distractions. A taxonomy of the sources of bus driver distraction identified is presented, along with a discussion of proposed countermeasures designed to remove the sources identified or mitigate their effects on driver performance.     

Parallel Implementation of a Class of Adaptive Signal Processing Applications

Recently, High Performance Computing (HPC) platforms have been employed to realize many computationally demanding applications in signal and image processing. These applications require real-time performance constraints to be met. These constraints include latency as well as throughput. In order to meet these performance requirements, efficient parallel algorithms are needed. These algorithms must be engineered to exploit the computational characteristics of such applications. In this paper we present a methodology for mapping a class of adaptive signal processing applications onto HPC platforms such that the throughput performance is optimized. We first define a new task model using the salient computational characteristics of a class of adaptive signal processing applications. Based on this task model, we propose a new execution model. In the earlier linear pipelined execution model, the task mapping choices were restricted. The new model permits flexible task mapping choices, leading to improved throughput performance compared with the previous model. Using the new model, a three-step task mapping methodology is developed. It consists of (1) a data remapping step, (2) a coarse resource allocation step, and (3) a fine performance tuning step. The methodology is demonstrated by designing parallel algorithms for modern radar and sonar signal processing applications. These are implemented on IBM SP2 and Cray T3E, state-of-the-art HPC platforms, to show the effectiveness of our approach. Experimental results show significant performance improvement over those obtained by previous approaches. Our code is written using C and the Message Passing Interface (MPI). Thus, it is portable across various HPC platforms. Received April 8, 1998; revised February 2, 1999.     

Work and fatigue characteristics of unsuited and suited humans during isolated isokinetic joint motions

The effects of a pressurized suit on human performance were investigated. The suit is known as an Extra-Vehicular Mobility Unit (EMU) and is worn by astronauts while working outside their spacecraft in a low earth orbit. Isolated isokinetic joint torques of three female and three male subjects (all experienced users of the suit in 1G gravity) were measured while working at 100% and 80% of their maximum voluntary torque (MVT, which is synonymous with maximum voluntary contraction (MVC)). It was found that the average decrease in the total amount of work (the sum of the work in each repetition until fatigue) done when the subjects were wearing the EMU were 48% and 41% while working at 100% and 80% MVT, respectively. There is a clear relationship between the MVT and the time and amount of work done until fatigue. Here, the time to fatigue is defined as the ending time of the repetition for which the computed work done during that repetition dropped below 50% of the work done during the first repetition. In general the stronger joints took longer to fatigue and did more work than the weaker joints. It was found that the EMU decreases the work output at the wrist and shoulder joints the most, due to the EMU joint geometry. The EMU also decreased the joint range of motion. The average total amount of work done by the test subjects increased by 5.2% (20.4%) for the unsuited (suited) case, when the test subjects decreased the level of effort from 100% to 80% MVT. Also, the average time to fatigue increased by 9.2% (25.6%) for the unsuited (suited) case, when the test subjects decreased the level of effort from 100% to 80% MVT. It was also found that the experimentally measured torque decay could be predicted by a logarithmic equation. The absolute average errors in the predictions were found to be 18.3% and 18.9% for the unsuited and suited subjects, respectively, when working at 100% MVT, and 22.5% and 18.8% for the unsuited and suited subjects, respectively, when working at 80% MVT. These results could be very useful in the design of future EMU suits and the planning of Extra-Vehicular Activity (EVA) for the future International Space Station assembly operations.