Contextual Deliberation of Cognitive Agents in Defeasible Logic

This article extends Defeasible Logic to deal with the contextual deliberation process of cognitive agents. First, we introduce meta-rules to reason with rules. Meta-rules are rules that have as a consequent rules for motivational components, such as obligations, intentions and desires. In other words, they include nested rules. Second, we introduce explicit preferences among rules. They deal with complex structures where nested rules can be involved.

Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

An improved seeded region growing algorithm

Recently Adams and Bischof (1994) proposed a novel region growing algorithm for segmenting intensity images. The inputs to the algorithm are the intensity image and a set of seeds - individual points or connected components - that identify the individual regions to be segmented. The algorithm grows these seed regions until all of the image pixels have been assimilated. Unfortunately the algorithm is inherently dependent on the order of pixel processing. This means, for example, that raster order processing and anti-raster order processing do not, in general, lead to the same tessellation. In this paper we propose an improved seeded region growing algorithm that retains the advantages of the Adams and Bischof algorithm fast execution, robust segmentation, and no tuning parameters - but is pixel order independent. (C) 1997 Elsevier Science B.V.

Gaze angle: a possible mechanism of visual stress in virtual reality headsets

It is known that some Virtual Reality (VR) head-mounted displays (HMDs) can cause temporary deficits in binocular vision. On the other hand, the precise mechanism by which visual stress occurs is unclear. This paper is concerned with a potential source of visual stress that has not been previously considered with regard to VR systems: inappropriate vertical gaze angle. As vertical gaze angle is raised or lowered the 'effort' required of the binocular system also changes. The extent to which changes in vertical gaze angle alter the demands placed upon the vergence eye movement system was explored. The results suggested that visual stress may depend, in part, on vertical gaze angle. The proximity of the display screens within an HMD means that a VR headset should be in the correct vertical location for any individual user. This factor may explain some previous empirical results and has important implications for headset design. Fortuitously, a reasonably simple solution exists.

Effect of load distance on self-selected manual lifting technique

The aim of this research is to determine the effects of constraining the horizontal distance of the feet from the load on the posture adopted at the start of the lift. Kinematic data were collected while each of 24 subjects lifted 3, 6, and 9 kg loads from a starting height 18 cm above the ground. The position of the feet was controlled relative to the load such that the horizontal distance from the hand to the ankle at the start of extension was either 20, 40, or 60 cm. Subjects performed 20 trials in each of six combinations of load and ankle-load distance chosen to provide three sets of equivilent load moment pairs. The initial horizontal distance from the load to the ankle had a large influence on the posture adopted to lift the load. Ankle and knee flexion, in particular, were reduced when the ankle-load distance was smaller, and particularly so when the distance was reduced to 20 cm. Hip flexion was reduced to a smaller extent, while lumbar vertebral flexion remained relatively unchanged. The inclination of the trunk at the start of the lift was unchanged when the ankle-load distance was 60 or 40 cm, but was 10 degrees greater when the load was 20 cm from the ankles, indicating that subjects adopted a posture closer to a stoop when the ankle-load distance was small. Comparison of conditions of equal load moment (but different load mass and ankle-load distance) revealed differences which mirrored the effects of ankle-load distance alone, suggesting that the effects of ankle-load distance on the posture adopted at the start of extension were largely independent of the load moment. While the forces and torques required to lift a load must be to some extent dependent on the load moment, rather than load or ankle-load distance per se, the posture adopted to lift the load is not.

An exploration of varieties of visual attention: ERP findings

A set of five tasks was designed to examine dynamic aspects of visual attention: selective attention to color, selective attention to pattern, dividing and switching attention between color and pattern, and selective attention to pattern with changing target. These varieties of visual attention were examined using the same set of stimuli under different instruction sets; thus differences between tasks cannot be attributed to differences in the perceptual features of the stimuli. ERP data are presented for each of these tasks. A within-task analysis of different stimulus types varying in similarity to the attended target feature revealed that an early frontal selection positivity (FSP) was evident in selective attention tasks, regardless of whether color was the attended feature. The scalp distribution of a later posterior selection negativity (SN) was affected by whether the attended feature was color or pattern. The SN was largely unaffected by dividing attention across color and pattern. A large widespread positivity was evident in most conditions, consisting of at least three subcomponents which were differentially affected by the attention conditions. These findings are discussed in relation to prior research and the time course of visual attention processes in the brain. (C) 1999 Elsevier Science B.V. All rights reserved.

A comparative study of the fluidized-bed coating of cylindrical metal surfaces with various thermoplastic polymer powders

This paper reports the results of an experimental investigation into the fluidized-bed coating of cylindrical metal specimens using two types of thermoplastic powders, Rilsan(R) PA11, a nylon-11 powder produced by Elf Atochem, France and Cotene(TM) 4612, a linear low density polyethylene powder produced by J.R Courtenay (New Zealand). The effects of dipping time, preheat temperature and particle size distribution on coating thickness and surface finish were investigated. Consistent trends in coating thickness growth with dipping time were obtained for both nylon-11 and polyethylene powders with increases in coating thickness with preheat temperature. For the same preheat temperature, the lower melting point of polyethylene results in thicker coatings compared to those of nylon-11. There is a negligible change in the coating thickness for sieved powders compared to that for unsieved powders. A pre-heat temperatures of between 240 degrees C and 300 degrees C is necessary to achieve an acceptable surface finish with both nylon-11 and polyethylene powders. To minimize errors in achieving the desired coating thickness, dipping times shorter than 2 s are not recommended. The use of graphs of coating thickness versus dipping time in combination with the coating surface roughness plots presented in this paper enable the optimal choice of pre-heat temperature and dipping time to achieve acceptable surface finish. (C) 1999 Elsevier Science S.A. All rights reserved.

Programming internet based DAI applications in Qu-Prolog

This paper presents the unique collection of additional features of Qu-Prolog, a variant of the Al programming language Prolog, and illustrates how they can be used for implementing DAI applications. By this we mean applications comprising communicating information servers, expert systems, or agents, with sophisticated reasoning capabilities and internal concurrency. Such an application exploits the key features of Qu-Prolog: support for the programming of sound non-clausal inference systems, multi-threading, and high level inter-thread message communication between Qu-Prolog query threads anywhere on the internet. The inter-thread communication uses email style symbolic names for threads, allowing easy construction of distributed applications using public names for threads. How threads react to received messages is specified by a disjunction of reaction rules which the thread periodically executes. A communications API allows smooth integration of components written in C, which to Qu-Prolog, look like remote query threads.

Knowledge discovery and data mining in biological databases

The new technologies for Knowledge Discovery from Databases (KDD) and data mining promise to bring new insights into a voluminous growing amount of biological data. KDD technology is complementary to laboratory experimentation and helps speed up biological research. This article contains an introduction to KDD, a review of data mining tools, and their biological applications. We discuss the domain concepts related to biological data and databases, as well as current KDD and data mining developments in biology.

Context-free and context-sensitive dynamics in recurrent neural networks

Continuous-valued recurrent neural networks can learn mechanisms for processing context-free languages. The dynamics of such networks is usually based on damped oscillation around fixed points in state space and requires that the dynamical components are arranged in certain ways. It is shown that qualitatively similar dynamics with similar constraints hold for a(n)b(n)c(n), a context-sensitive language. The additional difficulty with a(n)b(n)c(n), compared with the context-free language a(n)b(n), consists of 'counting up' and 'counting down' letters simultaneously. The network solution is to oscillate in two principal dimensions, one for counting up and one for counting down. This study focuses on the dynamics employed by the sequential cascaded network, in contrast to the simple recurrent network, and the use of backpropagation through time. Found solutions generalize well beyond training data, however, learning is not reliable. The contribution of this study lies in demonstrating how the dynamics in recurrent neural networks that process context-free languages can also be employed in processing some context-sensitive languages (traditionally thought of as requiring additional computation resources). This continuity of mechanism between language classes contributes to our understanding of neural networks in modelling language learning and processing.

Labelled tableaux for non-normal modal logics

In this paper we show how to extend KEM, a tableau-like proof system for normal modal logic, in order to deal with classes of non-normal modal logics, such as monotonic and regular, in a uniform and modular way.

Visualization of learning in multilayer perceptron networks using principal component analysis

This paper is concerned with the use of scientific visualization methods for the analysis of feedforward neural networks (NNs). Inevitably, the kinds of data associated with the design and implementation of neural networks are of very high dimensionality, presenting a major challenge for visualization. A method is described using the well-known statistical technique of principal component analysis (PCA). This is found to be an effective and useful method of visualizing the learning trajectories of many learning algorithms such as back-propagation and can also be used to provide insight into the learning process and the nature of the error surface.

Genetic algorithms for design of liquid retaining structure

In this paper, genetic algorithm (GA) is applied to the optimum design of reinforced concrete liquid retaining structures, which comprise three discrete design variables, including slab thickness, reinforcement diameter and reinforcement spacing. GA, being a search technique based on the mechanics of natural genetics, couples a Darwinian survival-of-the-fittest principle with a random yet structured information exchange amongst a population of artificial chromosomes. As a first step, a penalty-based strategy is entailed to transform the constrained design problem into an unconstrained problem, which is appropriate for GA application. A numerical example is then used to demonstrate strength and capability of the GA in this domain problem. It is shown that, only after the exploration of a minute portion of the search space, near-optimal solutions are obtained at an extremely converging speed. The method can be extended to application of even more complex optimization problems in other domains.

RFID adoption: framework and survey in large Brazilian companies

Purpose - The purpose of this paper is to provide a framework for radio frequency identification (RFID) technology adoption considering company size and five dimensions of analysis: RFID applications, expected benefits business drivers or motivations barriers and inhibitors, and organizational factors. Design/methodology/approach - A framework for RFID adoption derived from literature and the practical experience on the subject is developed. This framework provides a conceptual basis for analyzing a survey conducted with 114 companies in Brazil. Findings - Many companies have been developing RFID initiatives in order to identify potential applications and map benefits associated with their implementation. The survey highlights the importance business drivers in the RFID implementation stage, and that companies implement RFID focusing on a few specific applications. However, there is a weak association between expected benefits and business challenges with the current level of RFID technology adoption in Brazil. Research limitations/implications - The paper is not exhaustive, since RFID adoption in Brazil is at early stages during the survey timeline. Originality/value - The main contribution of the paper is that it yields a framework for analyzing RFID technology adoption. The authors use this framework to analyze RFID adoption in Brazil, which proved to be a useful one for identifying key issues for technology adoption. The paper is useful to any researchers or practitioners who are focused on technology adoption, in particular, RFID technology.

Development Resource Planning: Complexity of Product Development and the Capacity to Launch New Products

Overcommitment of development capacity or development resource deficiencies are important problems in new product development (NPD). Existing approaches to development resource planning have largely neglected the issue of resource magnitude required for NPD. This research aims to fill the void by developing a simple higher-level aggregate model based on an intuitive idea: The number of new product families that a firm can effectively undertake is bound by the complexity of its products or systems and the total amount of resources allocated to NPD. This study examines three manufacturing companies to verify the proposed model. The empirical results confirm the study`s initial hypothesis: The more complex the product family, the smaller the number of product families that are launched per unit of revenue. Several suggestions and implications for managing NPD resources are discussed, such as how this study`s model can establish an upper limit for the capacity to develop and launch new product families.