The new localism, anti-political development machines, and the role of planning consultants: lessons from London's South Bank

This paper draws on a study of the politics of development planning in London’s South Bank to examine wider trends in the governance of contemporary cities. It assesses the impacts and outcomes of so-called new localist reforms and argues that we are witnessing two principal trends. First, governance processes are increasingly dominated by anti-democratic development machines, characterized by new assemblages of public- and private-sector experts. These machines reflect and reproduce a type of development politics in which there is a greater emphasis on a pragmatic realism and a politics of delivery. Second, the presence of these machines is having a significant impact on the politics of planning. Democratic engagement is not seen as the basis for new forms of localism and community control. Instead, it is presented as a potentially disruptive force that needs to be managed by a new breed of skilled private-sector consultant. The paper examines these wider shifts in urban politics before focusing on the connections between emerging development machines and local residential and business communities. It ends by highlighting some of the wider implications of change for democratic modes of engagement and nodes of resistance in urban politics.

Transmathematical basis of infinitely scalable pipeline machines

We describe infinitely scalable pipeline machines with perfect parallelism, in the sense that every instruction of an inline program is executed, on successive data, on every clock tick. Programs with shared data effectively execute in less than a clock tick. We show that pipeline machines are faster than single or multi-core, von Neumann machines for sufficiently many program runs of a sufficiently time consuming program. Our pipeline machines exploit the totality of transreal arithmetic and the known waiting time of statically compiled programs to deliver the interesting property that they need no hardware or software exception handling.

A scanning electron microscopy study of diseased root surfaces conditioned with EDTA gel plus Cetavlon after scaling and root planing

In the present investigation, a scanning electron microscopy analysis was performed to evaluate the effects of the topical application of ethylenediaminetetraacetic acid (EDTA) gel associated with Cetavlon (EDTAC) in removing the smear layer and exposing collagen fibers following root surface instrumentation. Twenty-eight teeth from adult humans, single rooted and scheduled for extraction due to periodontal reasons, were selected. Each tooth was submitted to manual (scaling and root planing) instrumentation alone or combined with ultrasonic instruments, with or without etching using a 24% EDTAC gel. Following extraction, specimens were processed and examined under a scanning electron microscope. A comparative morphological semi-quantitative analysis was performed; the intensity of the smear layer and the decalcification of cementum and dentinal surfaces were graded in 12 sets using an arbitrary scale ranging from 1 (area covered by a smear layer) to 4 (no smear layer). Root debridement with hand instruments alone or combined with ultrasonic instruments resulted in a similar smear layer covering the root surfaces. The smear layer was successfully removed from the surfaces treated with EDTAC, which exhibited numerous exposed dentinal tubules and collagen fibers. This study supports the hypothesis that manual instrumentation alone or instrumentation combined with ultrasonic instrumentation is unable to remove the smear layer, whereas the subsequent topical application of EDTAC gel effectively removes the smear layer, uncovers dentinal openings and exposes collagen fibers.

Checking Completeness of Tests for Finite State Machines

In testing from a Finite State Machine (FSM), the generation of test suites which guarantee full fault detection, known as complete test suites, has been a long-standing research topic. In this paper, we present conditions that are sufficient for a test suite to be complete. We demonstrate that the existing conditions are special cases of the proposed ones. An algorithm that checks whether a given test suite is complete is given. The experimental results show that the algorithm can be used for relatively large FSMs and test suites.

Road and Traffic Signs Recognition using Vector Machines

Intelligent Transportation System (ITS) is a system that builds a safe, effective and integrated transportation environment based on advanced technologies. Road signs detection and recognition is an important part of ITS, which offer ways to collect the real time traffic data for processing at a central facility.This project is to implement a road sign recognition model based on AI and image analysis technologies, which applies a machine learning method, Support Vector Machines, to recognize road signs. We focus on recognizing seven categories of road sign shapes and five categories of speed limit signs. Two kinds of features, binary image and Zernike moments, are used for representing the data to the SVM for training and test. We compared and analyzed the performances of SVM recognition model using different features and different kernels. Moreover, the performances using different recognition models, SVM and Fuzzy ARTMAP, are observed.