Prioritization Assessment of Housing Development Risk Factors: A Fuzzy Hierarchical Process-Based Approach

The construction industry and housing subsector are fraught with risks that have the potential of negatively impacting on the achievement of project objectives. The success or otherwise of most construction projects depends to large extent on how well these risks have been managed. The recent paradigm shift by the subsector to use of formal risk management approach in contrast to hitherto developed rules of thumb means that risks must not only be identified but also properly assessed and responded to in a systematic manner. The study focused on identifying risks associated with housing development projects and prioritisation assessment of the identified risks in order to provide basis for informed decision. The study used a three-step identification framework: review of literature for similar projects, expert consultation and questionnaire based survey to identify potential risk factors. Delphi survey method was employed in carrying out the relative prioritization assessment of the risks factors using computer-based Analytical Hierarchical Process (AHP) software. The results show that 19 out of the 50 risks significantly impact on housing development projects. The study concludes that although significant numbers of risk factors have been identified as having relevance and impacting to housing construction projects, economic risk group and, in particular, ‘changes in demand for houses’ is prioritised by most developers as posing a threat to the achievement of their housing development objectives. Unless these risks are carefully managed, their effects will continue to impede success in these projects. The study recommends the adoption and use of the combination of multi-technique identification framework and AHP prioritization assessment methodology as a suitable model for the assessment of risks in housing development projects.

Performance and Emission Prediction in a Biodiesel Engine Fuelled with Honge Methyl Ester Using RBF Neural Networks

In the present study, RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tex and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Effect of Hydrogen-Diesel Dual Fuel Combustion on the Performance and Emission Characteristics of a Four Stroke-Single Cylinder Diesel Engine

The present work attempts to investigate the combustion, performance and emission characteristics of an existing single-cylinder four-stroke compression-ignition engine operated in dual-fuel mode with hydrogen as an alternative fuel. Environmental concerns and limited amount of petroleum fuels have caused interests in the development of alternative fuels like hydrogen for internal combustion (IC) engines. In this experimental investigation, a diesel engine is made to run using hydrogen in dual fuel mode with diesel, where hydrogen is introduced into the intake manifold using an LPGCNG injector and pilot diesel is injected using diesel injectors. A Timed Manifold Injection (TMI) system has been developed to vary the injection strategies. The optimized timing for the injection of hydrogen was 10^0 CA after top dead center (ATDC). From the study it was observed that with increasing hydrogen rate, enhancement in brake thermal efficiency (BTHE) of the engine has been observed with reduction in brake specific energy consumption (BSEC). Furthermore, Soot contents decrease with an increase in indicated specific NOx emissions with the enhancement of hydrogen flow rate.

Eye-Gesture Analysis for Driver Hazard Awareness

Because road traffic accidents are a major source of death worldwide, attempts have been made to create Advanced Driver Assistance Systems (ADAS) able to detect vehicle, driver and environmental conditions that are cues for possible potential accidents. This paper presents continued work on a novel Nonintrusive Intelligent Driver Assistance and Safety System (Ni-DASS) for assessing driver attention and hazard awareness. It uses two onboard CCD cameras – one observing the road and the other observing the driver-s face. The windscreen is divided into cells and analysis of the driver-s eye-gaze patterns allows Ni-DASS to determine the windscreen cell the driver is focusing on using eye-gesture templates. Intersecting the driver-s field of view through the observed windscreen cell with subsections of the camera-s field of view containing a potential hazard allows Ni-DASS to estimate the probability that the driver has actually observed the hazard. Results have shown that the proposed technique is an accurate enough measure of driver observation to be useful in ADAS systems.

Microwave LNA Design Based On Adaptive Network Fuzzy Inference and Evolutionary Optimization

This paper presents a novel approach for the design of microwave circuits using Adaptive Network Fuzzy Inference Optimizer (ANFIO). The method takes advantage of direct synthesis of subsections of the amplifier using very fast and accurate ANFIO models based on exact simulations using ADS. A mapping from course space to fine space known as space mapping is also used. The proposed synthesis approach takes into account the noise and scattering parameters due to parasitic elements to achieve optimal results. The overall ANFIO system is capable of designing different LNAs at different noise and scattering criteria. This approach offers significantly reduced time in the design of microwave amplifiers within the validity range of the ANFIO system. The method has been proven to work efficiently for a 2.4GHz LNA example. The S21 of 10.1 dB and noise figure (NF) of 2.7 dB achieved for ANFIO while S21 of 9.05 dB and NF of 2.6 dB achieved for ANN.

Improvement of Learning Motivation and Negotiation of Learning Disorders of Students Using Integrative Teaching Methodology

Integrative teaching methodology is based on connecting and summarizing knowledge from different subjects in order to create better understanding of different disciplines and improvement of competences in general. Integrative teaching methodology was implemented and realised during one academic year in 17 Latvian schools according with specially worked out programme by specialists of different fields for adaptation in social environment of children and young people with learning, cognitive functions and motor disorders. Implemented integrative teaching methodology consisted from three subsections which were specialised for adaptation in social environment, improvement of cognitive functions and improvement and harmonization of personality. The results of investigation showed that the use of integrative teaching methodology is an effective way for improvement of learning motivation and negotiation of learning disorders of different age schoolchildren.

Hydrogen and Diesel Combustion on a Single Cylinder Four Stroke Diesel Engine in Dual Fuel mode with Varying Injection Strategies

The present energy situation and the concerns about global warming has stimulated active research interest in non-petroleum, carbon free compounds and non-polluting fuels, particularly for transportation, power generation, and agricultural sectors. Environmental concerns and limited amount of petroleum fuels have caused interests in the development of alternative fuels for internal combustion (IC) engines. The petroleum crude reserves however, are declining and consumption of transport fuels particularly in the developing countries is increasing at high rates. Severe shortage of liquid fuels derived from petroleum may be faced in the second half of this century. Recently more and more stringent environmental regulations being enacted in the USA and Europe have led to the research and development activities on clean alternative fuels. Among the gaseous fuels hydrogen is considered to be one of the clean alternative fuel. Hydrogen is an interesting candidate for future internal combustion engine based power trains. In this experimental investigation, the performance and combustion analysis were carried out on a direct injection (DI) diesel engine using hydrogen with diesel following the TMI(Time Manifold Injection) technique at different injection timings of 10 degree,45 degree and 80 degree ATDC using an electronic control unit (ECU) and injection durations were controlled. Further, the tests have been carried out at a constant speed of 1500rpm at different load conditions and it can be observed that brake thermal efficiency increases with increase in load conditions with a maximum gain of 15% at full load conditions during all injection strategies of hydrogen. It was also observed that with the increase in hydrogen energy share BSEC started reducing and it reduced to a maximum of 9% as compared to baseline diesel at 10deg ATDC injection during maximum injection proving the exceptional combustion properties of hydrogen.