Do wordnets also improve human performance on NLP tasks?

FinnWordNet is a wordnet for Finnish that complies with the format of the Princeton WordNet (PWN) (Fellbaum, 1998). It was built by translating the PrincetonWordNet 3.0 synsets into Finnish by human translators. It is open source and contains 117000 synsets. The Finnish translations were inserted into the PWN structure resulting in a bilingual lexical database. In natural language processing (NLP), wordnets have been used for infusing computers with semantic knowledge assuming that humans already have a sufficient amount of this knowledge. In this paper we present a case study of using wordnets as an electronic dictionary. We tested whether native Finnish speakers benefit from using a wordnet while completing English sentence completion tasks. We found that using either an English wordnet or a bilingual English Finnish wordnet significantly improves performance in the task. This should be taken into account when setting standards and comparing human and computer performance on these tasks.

Optimal control predicts human performance on objects with internal degrees of freedom.

On a daily basis, humans interact with a vast range of objects and tools. A class of tasks, which can pose a serious challenge to our motor skills, are those that involve manipulating objects with internal degrees of freedom, such as when folding laundry or using a lasso. Here, we use the framework of optimal feedback control to make predictions of how humans should interact with such objects. We confirm the predictions experimentally in a two-dimensional object manipulation task, in which subjects learned to control six different objects with complex dynamics. We show that the non-intuitive behavior observed when controlling objects with internal degrees of freedom can be accounted for by a simple cost function representing a trade-off between effort and accuracy. In addition to using a simple linear, point-mass optimal control model, we also used an optimal control model, which considers the non-linear dynamics of the human arm. We find that the more realistic optimal control model captures aspects of the data that cannot be accounted for by the linear model or other previous theories of motor control. The results suggest that our everyday interactions with objects can be understood by optimality principles and advocate the use of more realistic optimal control models for the study of human motor neuroscience.

An evaluation of sleep hypnotic and stimulant effect on human performance using a computerized psychological test battery

This study evaluated the administration-time-dependent effects of a stimulant (Dexedrine 5-mg), a sleep-inducer (Halcion 0.25-mg) and placebo (control) on human performance. The investigation was conducted on 12 diurnally active (0700-2300) male adults (23-38 yrs) using a double-blind, randomized sixway-crossover three-treatment, two-timepoint (0830 vs 2030) design. Performance tests were conducted hourly during sleepless 13-hour studies using a computer generated, controlled and scored multi-task cognitive performance assessment battery (PAB) developed at the Walter Reed Army Institute of Research. Specific tests were Simple and Choice Reaction Time, Serial Addition/Subtraction, Spatial Orientation, Logical Reasoning, Time Estimation, Response Timing and the Stanford Sleepiness Scale. The major index of performance was "Throughput", a combined measure of speed and accuracy.^ For the Placebo condition, Single and Group Cosinor Analysis documented circadian rhythms in cognitive performance for the majority of tests, both for individuals and for the group. Performance was best around 1830-2030 and most variable around 0530-0700 when sleepiness was greatest (0300).^ Morning Dexedrine dosing marginally enhanced performance an average of 3% with reference to the corresponding in time control level. Dexedrine AM also increased alertness by 10% over the AM control. Dexedrine PM failed to improve performance with reference to the corresponding PM control baseline. With regard to AM and PM Dexedrine administrations, AM performance was 6% better with subjects 25% more alert.^ Morning Halcion administration caused a 7% performance decrement and 16% increase in sleepiness and a 13% decrement and 10% increase in sleepiness when administered in the evening compared to corresponding in time control data. Performance was 9% worse and sleepiness 24% greater after evening versus morning Halcion administration.^ These results suggest that for evening Halcion dosing, the overnight sleep deprivation occurring in coincidence with the nadir in performance due to circadian rhythmicity together with the CNS depressant effects combine to produce performance degradation. For Dexedrine, morning administration resulted in only marginal performance enhancement; Dexedrine in the evening was less effective, suggesting the 5-mg dose level may be too low to counteract the partial sleep deprivation and nocturnal nadir in performance. ^

Measuring human performance.

"Preliminary draft."

Modelling human performance within manufacturing systems design:from a theoretical towards a practical framework

Computer-based simulation is frequently used to evaluate the capabilities of proposed manufacturing system designs. Unfortunately, the real systems are often found to perform quite differently from simulation predictions and one possible reason for this is an over-simplistic representation of workers' behaviour within current simulation techniques. The accuracy of design predictions could be improved through a modelling tool that integrates with computer-based simulation and incorporates the factors and relationships that determine workers' performance. This paper explores the viability of developing a similar tool based on our previously published theoretical modelling framework. It focuses on evolving this purely theoretical framework towards a practical modelling tool that can actually be used to expand the capabilities of current simulation techniques. Based on an industrial study, the paper investigates how the theoretical framework works in practice, analyses strengths and weaknesses in its formulation, and proposes developments that can contribute towards enabling human performance modelling in a practical way.

Improving the design process for factories:modelling human performance variation

Theprocess of manufacturing system design frequently includes modeling, and usually, this means applying a technique such as discrete event simulation (DES). However, the computer tools currently available to apply this technique enable only a superficial representation of the people that operate within the systems. This is a serious limitation because the performance of people remains central to the competitiveness of many manufacturing enterprises. Therefore, this paper explores the use of probability density functions to represent the variation of worker activity times within DES models.

Towards a theoretical framework for human performance modelling within manufacturing systems design

The performance of direct workers has a significant impact on the competitiveness of many manufacturing systems. Unfortunately, system designers are ill equipped to assess this impact during the design process. An opportunity exists to assist designers by expanding the capabilities of popular simulation modelling tools, and using them as a vehicle to better consider human factors during the process of system design manufacture. To support this requirement, this paper reports on an extensive review of literature that develops a theoretical framework, which summarizes the principal factors and relationships that such a modelling tool should incorporate.

Human performance modelling as an aid in the process of manufacturing system design

Manufacturing system design is an ongoing activity within industry. Modelling tools based on Discrete Event Simulation are often used by practitioners during this design cycle. However, such tools do not adequately model the behaviour of 'direct' workers in manufacturing environments. There is an important need to expand the capability of modelling to include the relationships between human centred factors (demography, attitudes, beliefs, etc), their working environment (physical and organizational), and their subsequent performance in terms of productive routines. Therefore, this paper describes research that has formed a pilot modelling methodology that is an important first step in providing such a capability.