Fuzzy logic traffic control at a road junction with time-varying flow rates

Fuzzy logic has been applied to control traffic at road junctions. A simple controller with one fixed rule-set is inadequate to minimise delays when traffic flow rate is time-varying and likely to span a wide range. To achieve better control, fuzzy rules adapted to the current traffic conditions are used.

Hierarchical fuzzy logic traffic control at a road junction

Traffic control at road junctions is one of the major concerns in most metropolitan cities. Controllers of various approaches are available and the required control action is the effective green-time assigned to each traffic stream within a traffic-light cycle. The application of fuzzy logic provides the controller with the capability to handle uncertain natures of the system, such as drivers’ behaviour and random arrivals of vehicles. When turning traffic is allowed at the junction, the number of phases in the traffic-light cycle increases. The additional input variables inevitably complicate the controller and hence slow down the decision-making process, which is critical in this real-time control problem. In this paper, a hierarchical fuzzy logic controller is proposed to tackle this traffic control problem at a 2-way road junction with turning traffic. The two levels of fuzzy logic controllers devise the minimum effective green-time and fine-tune it respectively at each phase of a traffic-light cycle. The complexity of the controller at each level is reduced with smaller rule-set. The performance of this hierarchical controller is examined by comparison with a fixed-time controller under various traffic conditions. Substantial delay reduction has been achieved as a result and the performance and limitation of the controller will be discussed.

Semantic oscillations : encoding context and structure in complex valued holographic vectors

In computational linguistics, information retrieval and applied cognition, words and concepts are often represented as vectors in high dimensional spaces computed from a corpus of text. These high dimensional spaces are often referred to as Semantic Spaces. We describe a novel and efficient approach to computing these semantic spaces via the use of complex valued vector representations. We report on the practical implementation of the proposed method and some associated experiments. We also briefly discuss how the proposed system relates to previous theoretical work in Information Retrieval and Quantum Mechanics and how the notions of probability, logic and geometry are integrated within a single Hilbert space representation. In this sense the proposed system has more general application and gives rise to a variety of opportunities for future research.

Using upper bounds on attainable discrimination to select discrete valued features

Selection of features that will permit accurate pattern classification is a difficult task. However, if a particular data set is represented by discrete valued features, it becomes possible to determine empirically the contribution that each feature makes to the discrimination between classes. This paper extends the discrimination bound method so that both the maximum and average discrimination expected on unseen test data can be estimated. These estimation techniques are the basis of a backwards elimination algorithm that can be use to rank features in order of their discriminative power. Two problems are used to demonstrate this feature selection process: classification of the Mushroom Database, and a real-world, pregnancy related medical risk prediction task - assessment of risk of perinatal death.

Towards a single crystal Raman spectrum of kaolinite at 77 K

The Raman spectra at 77 K of the hydroxyl stretching of kaolinite were obtained along the three axes perpendicular to the crystal faces. Raman bands were observed at 3616, 3658 and 3677 cm−1 together with a distinct band observed at 3691 cm−1 and a broad profile between 3695 and 3715 cm−1. The band at 3616 cm−1 is assigned to the inner hydroxyl. The bands at 3658 and 3677 cm−1 are attributed to the out-of-phase vibrations of the inner surface hydroxyls. The Raman spectra of the in-phase vibrations of the inner-surface hydroxyl-stretching region are described in terms of transverse and longitudinal optic splitting. The band at 3691 cm−1 is assigned to the transverse optic and the broad profile to the longitudinal optic mode. This splitting remained even at liquid nitrogen temperature. The transverse optic vibration may be curve resolved into two or three bands, which are attributed to different types of hydroxyl groups in the kaolinite.

K-tree : large scale document clustering

We introduce K-tree in an information retrieval context. It is an efficient approximation of the k-means clustering algorithm. Unlike k-means it forms a hierarchy of clusters. It has been extended to address issues with sparse representations. We compare performance and quality to CLUTO using document collections. The K-tree has a low time complexity that is suitable for large document collections. This tree structure allows for efficient disk based implementations where space requirements exceed that of main memory.

The knowledge advantage (K-Adv): unleashing creativity and innovation

The K-Adv has been developed around the concept that it comprises an ICT enabling infrastructure that encompasses ICT hardware and software infrastructure facilities together with an enabling ICT support system; a leadership infrastructure support system that provides the vision for its implementation and the realisation capacity for the vision to be realised; and the necessary people infrastructure that includes the people capabilities and capacities supported by organisational processes that facilitates this resource to be mobilised.