Labour Productivity in the New Zealand Construction Industry: A Thorough Investigation

Productivity growth is strongly correlated to economic growth and increases in welfare. This fact also holds true at the industry level and is particularly true in the NZ construction industry, since productivity growth in this sector may have significant effects on the affordability of housing in the country. In recent years construction in NZ has been subjected to a series of reports that have either highlighted ‘failure’ to grow productivity or have exhorted the industry to improve its ‘poor performance’.  However thus far little by way of analysis has gone into the productivity figures that have been quoted, nor has much been done to explain and justify if or why these figures are correct or incorrect.This research seeks to deconstruct construction productivity figures in NZ and explain the patterns over recent years of ‘poor performance’ in comparison with other industries.  As such it will examine the nature of the NZ construction industry and analyse the historic statistics related to its labour productivity. This will provide an overall understanding of the sector as well as those extraneous factors that may have significant influences on the NZ construction sector.The research found that while factors influencing inputs of labour productivity measure such as labour and material costs remained stable, factors impacting the corresponding outputs such as house and land prices, value of work in Non-residential and Infrastructure construction grew significantly between 1997 and 2007. Given the positive skewing effect of standard economic indicators (inflation etc) on construction labour productivity figures, the relatively poor performance of construction is worrying for the industry. The paper concludes by demonstrating labour productivity in construction is significantly worse performing than previously suspected

A survey of data recovery on flash memory

In recent years, flash memory has become more widely used due to its advantages, such as fast data access, low power consumption, and high mobility. However, flash memory also has drawbacks that need to be overcome, such as erase-before-write, and the limitations of block deletion. In order to address this issue, the FTL (Flash Translation Layer) has been proposed with useful functionalities like address mapping, garbage collection, and wear-leveling. During the process of using, the data may be lost on power failure in the storage systems. In some systems, the data is very important. Thus recovery of data in the event of the system crash or a sudden power outage is of prime importance. This problem has attracted attention from researchers and many studies have been done. In this paper, we investigate previous studies on data recovery for flash memory from FTL processing solutions to PLR (Power Loss Recovery) solutions that have been proposed by authors in the conference proceeding, patents, or professional journals. This will provide a discussion of the proposed solutions to the data recovery in flash memory as well as an overview

Evaluating the Economics of Construction and Demolition Waste Minimisation and Zero Waste in the New Zealand Construction Industry

Currently, up to 50% of construction and demolition (C&D) waste is disposed of in landfills contributing to significant environmental, social and economic costs to New Zealand. However, current understanding of C&D costs is poor both internationally and within New Zealand. This thesis addresses this deficit by developing a framework to evaluate the economics of C&D waste minimisation. An understanding gained from this research could help New Zealand develop appropriate strategies to address C&D waste issues. As the research problem is complex and wide-ranging, this study used a mixed-method approach. Semi-structured elite interviews with highly experienced construction personnel were used to identify factors affecting a C&D waste minimisation strategy. This also established the context of the economic evaluation framework. Economic modelling was subsequently employed to develop the economic evaluation framework. The framework was then applied on two case studies: 1) a development of a large education facility and 2) a refurbishment of a commercial office space. The study found that: 1. a C&D waste landfill/cleanfill charge of $150 per tonne can a) deter construction from disposing of waste; and b) force construction to rethink waste disposal 2. C&D waste minimisation can offer clients benefits including tangible returns (i.e. cost savings) and intangible potentials (i.e. increased reputation) 3. there are costs of implementing C&D waste minimisation - but benefits gained can outweigh such costs; and 4. the optimal rate of reduction for C&D waste in the non-residential projects studied was 71% - 78% Overall, this research has made a contribution to knowledge through the development of a robust economic evaluation framework. Moreover, the study has also provided an impetus for future work in C&D waste minimisation economics in New Zealand

Effects of Data Standardization on Hyperparameter Optimization with the Grid Search Algorithm Based on Deep Learning: A Case Study of Electric Load Forecasting

This study investigates data standardization methods based on the grid search (GS) algorithm for energy load forecasting, including zero-mean, min-max, max, decimal, sigmoid, softmax, median, and robust, to determine the hyperparameters of deep learning (DL) models. The considered DL models are the convolutional neural network (CNN) and long short-term memory network (LSTMN). The procedure is made over (i) setting the configuration for CNN and LSTMN, (ii) establishing the hyperparameter values of CNN and LSTMN models based on epoch, batch, optimizer, dropout, filters, and kernel, (iii) using eight data standardization methods to standardize the input data, and (iv) using the GS algorithm to search the optimal hyperparameters based on the mean absolute error (MAE) and mean absolute percent error (MAPE) indexes. The effectiveness of the proposed method is verified on the power load data of the Australian state of Queensland and Vietnamese Ho Chi Minh city. The simulation results show that the proposed data standardization methods are appropriate, except for the zero-mean and min-max methods

Grid search of multilayer perceptron based on the walk-forward validation methodology

Multilayer perceptron neural network is one of the widely used method for load forecasting. There are hyperparameters which can be used to determine the network structure and used to train the multilayer perceptron neural network model. This paper aims to propose a framework for grid search model based on the walk-forward validation methodology. The training process will specify the optimal models which satisfy requirement for minimum of accuracy scores of root mean square error, mean absolute percentage error and mean absolute error. The testing process will evaluate the optimal models along with the other ones. The results indicated that the optimal models have accuracy scores near the minimum values. The US airline passenger and Ho Chi Minh city load demand data were used to verify the accuracy and reliability of the grid search framework

Greenhouse gas emissions from piggery and biogas digesters in the Red River Delta of Vietnam

High demand for pork consumption in Vietnam has led to a shift of pig production systems from smallholder to industrial-scale farms, particularly in the Red River Delta. This production intensification also produces massive manure and urine quantities, leading to water, air, and soil pollution. The use of biogas plants has been seen as efficient to achieve in the same time a decrease in pollution, and a provision of biogas resources and bio-organic fertilizers. However, increasing pig head density has been causing great pressure on biogas digesters, as their size is not big enough for treatments anymore. Inappropriate utilization and management of biogas digesters can not only cause losses from pig wastes, but also contributes to increase greenhouse gas (GHG) emissions such as carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). This case study aims to identify the role and contributions of biogas digesters to better manage the sources of GHG emissions from pig wastes for different types of pig farms. Four provinces of the Red River Delta were selected to test the pig waste management efficiency of biogas digesters and measure GHG emissions from these systems. The findings show that CO2, CH4 and N2O emission rates from pig manure are at least twice as much what is allowed under the Vietnam national technical regulation on ambient air quality. However, the GHGs emission rate does not significantly differ between smallholder and industrial-scale farms in the four surveyed provinces. Sampling position (between inside piggeries and outside the outlet of biogas digesters) did not affect significantly GHG emissions rate. These results confirm that the pig waste management of biogas digesters for both smallholder and industrial-scale pig farms is not efficient and that efforts need to be invested to mitigate GHG emissions in pig production. Reducing pig density per piggery is highly recommended. The modification of biogas digester structure to separate solid pig manure and urine should also be considered. Otherwise, the application of other alternative aerobic or anaerobic digestion technologies should also be encouraged and promoted. Biogas digesters in pig production have a significant role to play in Vietnam government’s mitigation strategies, as well as from the perspective of biosafety and animal husbandry policies

Current medical product development for diagnosis, surgical planning and treatment in the areas of Neurosurgery, Orthopeadic and Dental-Cranio-Maxillofacial surgery in Vietnam

With the population of 86 million and good GDP growth in recent decades, the medical market in Vietnam is growing fast. However, most of the medical technology products are imported, and the number of locally manufactured ones is limited and they do not have the high competition capability in term of quality, quantity and types. In this paper, the current product development in Vietnam for diagnosis, surgical planning and treatment in the areas of Rehabilitation, Neurosurgery, Orthopeadic and Dental-Cranio-Maxillofacial surgery is presented. A roadmap for medical technology development in Vietnam is propose

Microfluidic Chip for Trapping Magnetic Nanoparticles and Heating in Terms of Biological Analysis

In this study, we reported the results of the design and the fabrication a planar coil in copper (square, a = 10 mm, 15mm high, 90 turns), these planar coils were integrated in a microfluidic chip for trapping magnetic nanoparticles and local heating applications. A small thermocouple (type K, 1 mm tip size) was put directly on top of the micro-channel in poly(dimethyl-siloxane) in order to measure the temperature inside the channel during applying current. The design of planar coils was based on optimizing the results of the magnetic calculation. The most suitable value of the magnetic field generated by the coil was calculated by ANSYS® software corresponded to the different distances from the coil surface to the micro-channel bottom (magnetic field strength Hmax = 825 A/m). The magnetic filed and heating relationship was balanced in order to manipulating the trapping magnetic nanoparticles and heating process. This design of the microfluidic chip can be used to develop a complex microfluidic chip using magnetic nanoparticles

Chemical composition and antibacterial activities of essential oils from fruits of Melicope pteleifolia (Champ. Ex Benth.) T.G. Hartley grown in Lam Dong Province, Vietnam

In the present study, chemical composition and antibacterial properties of essential oil obtained from the aerial parts of the Melicope pteleifolia (Champ. ex Benth.) T.G Hartley in Dalat were evaluated. Essential oil was isolated through hydro-distillation. Twenty-nine constituents comprising 100% of the essential oil were characterized by gas chromatography/mass spectrometry (GC-MS) techniques. The major compounds in the essential oil were (+)-Sabinene (34.73%), Cis-α-bergamotene (13.15%), Z-α-trans-bergamotol (5.28%), β-mycrene (4.98%), and 1,3,6-octatriene, 3,7-dimethyl-(4.71%). Antibacterial activities of Melicope pteleifolia essential oil were investigated against Gram-positive and-negative bacteria. Results showed significant activities against Streptococcus pyogenes and Escherichia coli using an agar well diffusion method. The application of this essential oil in preventing and eliminating bacteria could be useful in fields as medicine and cosmetics.