Expressions of the Calabrian diaspora in Calabrian Australian writing

Although a number of studies on Italian Australian literature have been produced they have to date taken little account of the perception of the diverse experiences of migrants from different Italian regions which display substantial linguistic and cultural diversity and have developed literary cultures both different from and coincidental to Italian national literary culture. The only extensive study that has examined the literary culture of a regional Italian migrant group in Australia is Rando La Cava (1983) which explores the oral dialect literature of the Aeolian communities in Wollongong, Sydney and Melbourne. Some general studies on Italian Australian literature have dealt with a few individual first generation Calabrian authors such as poet Luigi Strano and prose writer Alfredo Strano (both are cited in the Auslit database although their records need substantial updating) as well as the work of some second and subsequent generations writers such as John Bono and Teresa Crea (both also found in the Auslit database). This paper proposes to explore the extent to which texts produced by writers who are currently known to be of Calabrian origin demonstrate marked characteristics of what might be termed a Calabrian-Australian migration experience. Its point of departure are the theoretical issues raised by Joseph Pivato and Snwja Gunew relating to the attendant cultural dislocations of writers whose geographical and/or cultural traditions are based in CALD contexts and proposing a return to questions of both origins and belonging given that interrogations of the national emerge from both local communities and global diasporas. The way ahead in terms of analysing cultural texts of any kind seems to be to denaturalise the classificatory categories invoked to stabilize and legitimate all types of nation-buildin

Conclusion - The Italian Diaspora after the Second World War

The Conference at Bivongi followed on others that had raised some serious questions about the Italian diaspora that occurred after the Second World War. We asked contributors to submit papers in three broad divisions, the first relating to the migrants\u27 experience before departure, the second to experience in the host country, and the third to the cinematographic and literary interpretation of that experience. The papers contributed that successfully completed the peer review process are arranged in that sequence in this book

Effect Of Variation In Liquefied Petroleum Gas (LPG) Proportions In Spark Ignition Engine Emissions.

This paper presents an experimental investigation of a Liquefied Petroleum Gas (LPG) fueled four-stroke spark ignition engine. The primary objective of the study was to determine and quantify the exhaust emissions from the engine

Genset Optimization for Biomass Syngas Operation

Although biomass is underrepresented in current methods for power generation, it has great potential to help meet the growing need for clean energy. This chapter details the modification of a gasoline-powered two-stroke genset for operation on syngas from a woodchip-powered gasifier. Generator and engine modifications along with a flexible air/fuel control system are described. Results from genset operation indicate a sustainable power output of 360 W with a biomass consumption rate of approximately 6 kg/hour. Optimum power production was achieved at an air/fuel ratio close to 1. After several hours of operation the engine was disassembled and inspected, revealing significant deposits on the piston and crank case parts, indicating that the engine would require weekly maintenance under such operating conditions

Review of air fuel ratio prediction and control methods

Air pollution is one of main challenging issues nowadays that researchers have been trying to address.The emissions of vehicle engine exhausts are responsible for 50 percent of air pollution. Different types of emissions emit from vehicles including carbon monoxide, hydrocarbons, NOX, and so on. There is a tendency to develop strategies of engine control which work in a fast way. Accomplishing this task will result in a decrease in emissions which coupled with the fuel composition can bring about the best performance of the vehicle engine.Controlling the Air-Fuel Ratio (AFR) is necessary, because the AFR has an enormous impact on the effectiveness of the fuel and reduction of emissions.This paper is aimed at reviewing the recent studies on the prediction and control of the AFR, as a bulk of research works with different approaches, was conducted in this area.These approaches include both classical and modern methods, namely Artificial Neural Networks (ANN), Fuzzy Logic, and Neuro-Fuzzy Systems are described in this paper.The strength and the weakness of individual approaches will be discussed at length

Adaptive neuro-fuzzy model with fuzzy clustering for nonlinear prediction and control

Nonlinear systems have more complex manner and profoundness than linear systems.Thus, their analyses are much more difficult.This paper presents the use of neuro-fuzzy networks as means of implementing algorithms suitable for nonlinear black-box prediction and control.In engineering applications, two attractive tools have emerged recently.These two attractive tools are: the artificial neural networks and the fuzzy logic system. One area of particular importance is the design of networks capable of modeling and predicting the behavior of systems that involve complex, multi-variable processes.To illustrate the applicability of the neuro-fuzzy networks, a case study involving air-fuel ratio is presented here.Air- fuel ratio represents complex, nonlinear and stochastic behavior.To monitor the engine conditions, an adaptive neuro-fuzzy inference system (ANFIS) is used to capture the nonlinear connections between the air- fuel ratio and control parameters such manifold air pressure, throttle position, manifold air temperature, engine temperature, engine speed, and injection opening time.This paper describes a fuzzy clustering method to initialize the ANFIS

Modern methods in engine knock signal detection

In this paper, a review is given of some of the modern methods in the detection of knock in internal-combustion engines and some comparisons are made between these methods and the effectiveness of each one of them is indicated through a statement of the advantages and disadvantages of each method. In this way it will be possible to clarify how to deal with the original signal and the associated signal noise through some of the modern algorithms in the field of soft computing such as an Artificial Neural Network (ANN), Genetic Algorithms (GA), Wavelet Transform (WT), Fuzzy logic, Supported Vector Machine (SVM) and some statistical methods