Hypercapitalism:Political economy, electric identity, and authorial alienation

Hypercapitalism, with its "knowledge economy", is the form of capitalism under which thought itself is produced, commodified, and exchanged within the globally integrated system of communication technologies. As such, hypercapitalism may be seen as not so much a revolution, but rather an evolution: the progressively thorough, inexorable totalisation of social relations by Capital. The study on which this paper is based synthesises the sociological perspectives of Marx (1970, 1844/1975, 1846/1972, 1976, 1978, 1981) and Adorno (1951/1974, 1991; Horkheimer & Adorno, 1944/1998), and the Critical Discourse perspectives of Fairclough (1989, 1992) and Lemke (1995) to argue that alienated thought and language are the fundamental, irreducible commodity-forms of Cybersociety’s knowledge economy.

Do androids dream of electric chimera?

This paper describes the use of the Chimera Architecture as the basis for a generative rhythmic improvisation system that is intended for use in ensemble contexts. This interactive soft- ware system learns in real time based on an audio input from live performers. The paper describes the components of the Chimera Architecture including a novel analysis engine that uses prediction to robustly assess the rhythmic salience of the input stream. Analytical results are stored in a hierarchical structure that includes multiple scenarios which allow ab- stracted and alternate interpretations of the current metrical context. The system draws upon this Chimera Architecture when generating a musical response. The generated rhythms are intended to have a particular ambiguity in relation to the music performance by other members of the ensemble. Ambi- guity is controlled through alternate interpretations of the Chimera. We describe an implementation of the Chimera Ar- chitecture that focuses on rhythmic material, and present and discuss initial experimental results of the software system playing along with recordings of a live performance.

Temperature and electric field dependent mobility in poly„3-hexylthiophene diodes

Current-voltage (I-V) curves of Poly(3-hexyl-thiophene) (P3HT) diodes have been collected to investigate the polymer hole-dominated charge transport. At room temperature and at low electric fields the I-V characteristic is purely Ohmic whereas at medium-high electric fields, experimental data shows that the hole transport is Trap Dominated - Space Charge Limited Current (TD-SCLC). In this regime, it is possible to extract the I-V characteristic of the P3HT/Al junction showing the ideal Schottky diode behaviour over five orders of magnitude. At high-applied electric fields, holes’ transport is found to be in the trap free SCLC regime. We have measured and modelled in this regime the holes’ mobility to evaluate its dependence from the electric field applied and the temperature of the device.

On the optimal capacity expansion of electric power systems

The analysis of investment in the electric power has been the subject of intensive research for many years. The efficient generation and distribution of electrical energy is a difficult task involving the operation of a complex network of facilities, often located over very large geographical regions. Electric power utilities have made use of an enormous range of mathematical models. Some models address time spans which last for a fraction of a second, such as those that deal with lightning strikes on transmission lines while at the other end of the scale there are models which address time horizons consisting of ten or twenty years; these usually involve long range planning issues. This thesis addresses the optimal long term capacity expansion of an interconnected power system. The aim of this study has been to derive a new, long term planning model which recognises the regional differences which exist for energy demand and which are present in the construction and operation of power plant and transmission line equipment. Perhaps the most innovative feature of the new model is the direct inclusion of regional energy demand curves in the nonlinear form. This results in a nonlinear capacity expansion model. After review of the relevant literature, the thesis first develops a model for the optimal operation of a power grid. This model directly incorporates regional demand curves. The model is a nonlinear programming problem containing both integer and continuous variables. A solution algorithm is developed which is based upon a resource decomposition scheme that separates the integer variables from the continuous ones. The decompostion of the operating problem leads to an interactive scheme which employs a mixed integer programming problem, known as the master, to generate trial operating configurations. The optimum operating conditions of each trial configuration is found using a smooth nonlinear programming model. The dual vector recovered from this model is subsequently used by the master to generate the next trial configuration. The solution algorithm progresses until lower and upper bounds converge. A range of numerical experiments are conducted and these experiments are included in the discussion. Using the operating model as a basis, a regional capacity expansion model is then developed. It determines the type, location and capacity of additional power plants and transmission lines, which are required to meet predicted electicity demands. A generalised resource decompostion scheme, similar to that used to solve the operating problem, is employed. The solution algorithm is used to solve a range of test problems and the results of these numerical experiments are reported. Finally, the expansion problem is applied to the Queensland electricity grid in Australia.

On the optimal capacity expansion of electric power systems

The analysis of investment in the electric power has been the subject of intensive research for many years. The efficient generation and distribution of electrical energy is a difficult task involving the operation of a complex network of facilities, often located over very large geographical regions. Electric power utilities have made use of an enormous range of mathematical models. Some models address time spans which last for a fraction of a second, such as those that deal with lightning strikes on transmission lines while at the other end of the scale there are models which address time horizons consisting of ten or twenty years; these usually involve long range planning issues. This thesis addresses the optimal long term capacity expansion of an interconnected power system. The aim of this study has been to derive a new, long term planning model which recognises the regional differences which exist for energy demand and which are present in the construction and operation of power plant and transmission line equipment. Perhaps the most innovative feature of the new model is the direct inclusion of regional energy demand curves in the nonlinear form. This results in a nonlinear capacity expansion model. After review of the relevant literature, the thesis first develops a model for the optimal operation of a power grid. This model directly incorporates regional demand curves. The model is a nonlinear programming problem containing both integer and continuous variables. A solution algorithm is developed which is based upon a resource decomposition scheme that separates the integer variables from the continuous ones. The decompostion of the operating problem leads to an interactive scheme which employs a mixed integer programming problem, known as the master, to generate trial operating configurations. The optimum operating conditions of each trial configuration is found using a smooth nonlinear programming model. The dual vector recovered from this model is subsequently used by the master to generate the next trial configuration. The solution algorithm progresses until lower and upper bounds converge. A range of numerical experiments are conducted and these experiments are included in the discussion. Using the operating model as a basis, a regional capacity expansion model is then developed. It determines the type, location and capacity of additional power plants and transmission lines, which are required to meet predicted electicity demands. A generalised resource decompostion scheme, similar to that used to solve the operating problem, is employed. The solution algorithm is used to solve a range of test problems and the results of these numerical experiments are reported. Finally, the expansion problem is applied to the Queensland electricity grid in Australia

Application of reliability-centred maintenance technology on electric trains

This paper demonstrates the application of the reliability-centred maintenance (RCM) process to analyse and develop preventive maintenance tasks for electric multiple units (EMU) in the East Rail of the Kowloon-Canton Railway Corporation (KCRC). Two systems, the 25 kV electrical power supply and the air-conditioning system of the EMU, have been chosen for the study. RCM approach on the two systems is delineated step by step in the paper. This study confirms the feasibility and effectiveness of RCM applications on the maintenance of electric trains.

Reversed bias Pt/nanostructured ZnO Schottky diode with enhanced electric field for hydrogen sensing

In this paper, the effect of electric field enhancement on Pt/nanostructured ZnO Schottky diode based hydrogen sensors under reverse bias condition has been investigated. Current-voltage characteristics of these diodes have been studied at temperatures from 25 to 620 °C and their free carrier density concentration was estimated by exposing the sensors to hydrogen gas. The experimental results show a significantly lower breakdown voltage in reversed bias current-voltage characteristics than the conventional Schottky diodes and also greater lateral voltage shift in reverse bias operation than the forward bias. This can be ascribed to the increased localized electric fields emanating from the sharp edges and corners of the nanostructured morphologies. At 620 °C, voltage shifts of 114 and 325 mV for 0.06% and 1% hydrogen have been recorded from dynamic response under the reverse bias condition. © 2010 Elsevier B.V. All rights reserved.

Overlapping medical alarms are almost indiscriminable

Objective: We explore how accurately and quickly nurses can identify melodic medical equipment alarms when no mnemonics are used, when alarms may overlap, and when concurrent tasks are performed. Background: The international standard IEC 60601-1-8 (International Electrotechnical Commission, 2005) has proposed simple melodies to distinguish seven alarm sources. Previous studies with nonmedical participants reveal poor learning of melodic alarms and persistent confusions between some of them. The effects of domain expertise, concurrent tasks, and alarm overlaps are unknown. Method: Fourteen intensive care and general medical unit nurses learned the melodic alarms without mnemonics in two sessions on separate days. In the second half of Day 2 the nurses identified single alarms or pairs of alarms played in sequential, partially overlapping, or nearly completely overlapping configurations. For half the experimental blocks nurses performed a concurrent mental arithmetic task. Results: Nurses' learning was poor and was no better than the learning of nonnurses in a previous study. Nurses showed the previously noted confusions between alarms. Overlapping alarms were exceptionally difficult to identify. The concurrent task affected response time but not accuracy. Conclusion: Because of a failure of auditory stream segregation, the melodic alarms cannot be discriminated when they overlap. Directives to sequence the sounding of alarms in medical electrical equipment must be strictly adhered to, or the alarms must redesigned to support better auditory streaming. Application: Actual or potential uses of this research include the implementation of IEC 60601-1-8 alarms in medical electrical equipment.

Learnability and discriminability of melodic medical equipment alarms

Melodic alarms proposed in the IEC 60601-1-8 standard for medical electrical equipment were tested for learnability and discriminability. Thirty-three non-anaesthetist participants learned the alarms over two sessions of practice, with or without mnemonics suggested in the standard. Fewer than 30% of participants could identify the alarms with 100% accuracy at the end of practice. Confusions persisted between pairs of alarms, especially if mnemonics were used during learning (p = 0.011). Participants responded faster (p < 0.00001) and more accurately (p = 0.002) to medium priority alarms than to high priority alarms, even though they rated the high priority alarms as sounding more urgent (p < 0.00001). Participants with at least 1 year of formal musical training identified the alarms more accurately (p = 0.0002) than musically untrained participants, and found the task easier overall (p < 0.00001). More intensive studies of the IEC 60601-1-8 alarms are needed for their effectiveness to be determined.