Methods of Adaptive Extraction and Analysis of Knowledge for Knowledge-base Construction and Fast Decision Making

An approach for knowledge extraction from the information arriving to the knowledge base input and also new knowledge distribution over knowledge subsets already present in the knowledge base is developed. It is also necessary to realize the knowledge transform into parameters (data) of the model for the following decision-making on the given subset. It is assumed to realize the decision-making with the fuzzy sets’ apparatus.

New Advancements of Scalable Statistical Methods for Learning Latent Structures in Big Data

Constant technology advances have caused data explosion in recent years. Accord- ingly modern statistical and machine learning methods must be adapted to deal with complex and heterogeneous data types. This phenomenon is particularly true for an- alyzing biological data. For example DNA sequence data can be viewed as categorical variables with each nucleotide taking four different categories. The gene expression data, depending on the quantitative technology, could be continuous numbers or counts. With the advancement of high-throughput technology, the abundance of such data becomes unprecedentedly rich. Therefore efficient statistical approaches are crucial in this big data era.

Previous statistical methods for big data often aim to find low dimensional struc- tures in the observed data. For example in a factor analysis model a latent Gaussian distributed multivariate vector is assumed. With this assumption a factor model produces a low rank estimation of the covariance of the observed variables. Another example is the latent Dirichlet allocation model for documents. The mixture pro- portions of topics, represented by a Dirichlet distributed variable, is assumed. This dissertation proposes several novel extensions to the previous statistical methods that are developed to address challenges in big data. Those novel methods are applied in multiple real world applications including construction of condition specific gene co-expression networks, estimating shared topics among newsgroups, analysis of pro- moter sequences, analysis of political-economics risk data and estimating population structure from genotype data.

New methods for the asymmetric synthesis of α-alkylated ketones and 1,3-amino alcohols

A large number of optically active drugs and natural products contain α-functionalised ketones or simple derivatives thereof. Furthermore, chiral α-alkylated ketones are useful synthons and have found widespread use in total synthesis. The asymmetric alkylation of ketones represents one of the most powerful and longstanding procedures in organic chemistry. Surprisingly, however, only one effective methodology is available, and this involves the use of chiral auxiliaries. This is discussed in Chapter 1, which also provides a background of other key topics discussed throughout the thesis. Expanding on the existing methodology of chiral auxiliaries, Chapter 2 details the synthesis of a novel chiral auxiliary containing a pyrrolidine ring and its use in the asymmetric preparation of α-alkylated ketones with good enantioselectivity. The synthesis of racemic α-alkylated ketones as reference standards for GC chromatography is also reported in this chapter. Chapter 3 details a new approach to chiral α-alkylated ketones using an intermolecular chirality transfer methodology. This approach employs the use of simple non-chiral dimethylhydrazones and their asymmetric alkylation using the chiral diamine ligands, (+)- and (-)-sparteine. The methodology described represents the first example of an asymmetric alkylation of non-chiral azaenolates. Enantiomeric ratios up to 83 : 17 are observed. Chapter 4 introduces the first aldol-Tishchenko reaction of an imine derivative for the preparation of 1,3-aminoalcohol precursors. 1,3-Aminoalcohols can be synthesised via indirect routes involving various permutations of stepwise construction with asymmetric induction. Our approach offers an alternative highly diastereomeric route to the synthesis of this important moiety utilising N-tert-butanesulfinyl imines in an aldol-Tishchenko-type reaction. Chapter 5 details the experimental procedures for all of the above work. Chapter 6 discusses the results of a separate research project undertaken during this PhD. 2-alkyl-quinolin-4-ones and their N-substituted derivatives have several important biological functions such as the role of Pseudomonas quinolone signal (PQS) in quorum sensing. Herein, we report the synthesis of its biological precursor, 2-heptyl-4-hydroxy-quinoline (HHQ) and possible isosteres of PQS; the C-3 Cl, Br and I analogues. N-Methylation of the iodide was also feasible and the usefulness of this compound showcased in Pd-catalysed cross-coupling reactions, thus allowing access to a diverse set of biologically important molecules.

The development of a new four-year Construction Technology and Management Stream at QUT

This paper focuses on the development and delivery of a core construction management (CM) unit, which forms the capstone of a four-unit CM stream in an undergraduate programme in the Faculty of Built Environment and Engineering at the Queensland University of Technology. UDB410 (Construction Management) is a final year unit that consolidates skills students have learned throughout their degree, hopefully graduating them as work-ready construction managers. It was developed in consultation with the Queensland Chapter of the Australian Institute of Building (AIB) and is a final year unit in the undergraduate Bachelor of Urban Development (CM) course. The unit uses various tools such as the OSIRIS business database (Bureau van Dijk Electronic Publishing, 2009), the AROUSAL (UK Version) construction business simulation (Lansley, 2009) and the Denison Organisational Culture Survey (Denison, 2000) to facilitate the development of skills in managing a construction company. The objectives of the paper are: • To track the rationale and development of the UDB410 unit sand describe the way in which this final year unit integrates learning from other parts of the course within which it is located as well as capping-off the CM stream of core units; • To highlight the difficulties of blending a balance of technology and management in a single unit; and • To explain how partnering with the construction industry benefited the learning quality of the unit.

New criteria for evaluating methods of identifying hot spots

Identification of hot spots, also known as the sites with promise, black spots, accident-prone locations, or priority investigation locations, is an important and routine activity for improving the overall safety of roadway networks. Extensive literature focuses on methods for hot spot identification (HSID). A subset of this considerable literature is dedicated to conducting performance assessments of various HSID methods. A central issue in comparing HSID methods is the development and selection of quantitative and qualitative performance measures or criteria. The authors contend that currently employed HSID assessment criteria—namely false positives and false negatives—are necessary but not sufficient, and additional criteria are needed to exploit the ordinal nature of site ranking data. With the intent to equip road safety professionals and researchers with more useful tools to compare the performances of various HSID methods and to improve the level of HSID assessments, this paper proposes four quantitative HSID evaluation tests that are, to the authors’ knowledge, new and unique. These tests evaluate different aspects of HSID method performance, including reliability of results, ranking consistency, and false identification consistency and reliability. It is intended that road safety professionals apply these different evaluation tests in addition to existing tests to compare the performances of various HSID methods, and then select the most appropriate HSID method to screen road networks to identify sites that require further analysis. This work demonstrates four new criteria using 3 years of Arizona road section accident data and four commonly applied HSID methods [accident frequency ranking, accident rate ranking, accident reduction potential, and empirical Bayes (EB)]. The EB HSID method reveals itself as the superior method in most of the evaluation tests. In contrast, identifying hot spots using accident rate rankings performs the least well among the tests. The accident frequency and accident reduction potential methods perform similarly, with slight differences explained. The authors believe that the four new evaluation tests offer insight into HSID performance heretofore unavailable to analysts and researchers.

Sustainability performance of construction : conceptual models of satisfaction levels in construction projects

In general, the performance of construction projects, including their sustainability performance, does not meet optimal expectations. One aspect of this is the performance of the participants who are independent and make a significance impact on overall project outcomes. Of these participants, the client is traditionally the owner of the project, the architect or engineer is engaged as the lead designer and a contractor is selected to construct the facilities. Generally, the performance of the participants is gauged by considering three main factors, namely, time, cost and quality. As the level of satisfaction is a subjective issue, it is rarely used in the performance evaluation of construction work. Recently, various approaches to the measurement of satisfaction have been made in an attempt to determine the performance of construction project outcomes - for instance, client satisfaction, customer satisfaction, contractor satisfaction, occupant satisfaction and home buyer satisfaction. These not only identify the performance of the construction project but are also used to improve and maintain relationships. In addition, these assessments are necessary for the continuous improvement and enhanced cooperation of participants. The measurement of satisfaction levels primarily involves expectations and perceptions. An expectation can be regarded as a comparative standard of different needs, motives and beliefs, while a perception is a subjective interpretation that is influenced by moods, experiences and values. This suggests that the disparity between perceptions and expectations may possibly be used to represent different levels of satisfaction. However, this concept is rather new and in need of further investigation. This chapter examines the methods commonly practised in measuring satisfaction levels today and the advantages of promoting these methods. The results provide a preliminary review of the advantages of satisfaction measurement in the construction industry and recommendations are made concerning the most appropriate methods to use in identifying the performance of project outcomes.

Using game technologies to improve the safety of construction plant operations

Many accidents occur world-wide in the use of construction plant and equipment, and safety training is considered by many to be one of the best approaches to their prevention. However, current safety training methods/tools are unable to provide trainees with the hands-on practice needed. Game technology-based safety training platforms have the potential to overcome this problem in a virtual environment. One such platform is described in this paper - its characteristics are analysed and its possible contribution to safety training identified. This is developed and tested by means of a case study involving three major pieces of construction plant, which successfully demonstrates that the platform can improve the process and performance of the safety training involved in their operation. This research not only presents a new and useful solution to the safety training of construction operations, but illustrates the potential use of advanced technologies in solving construction industry problems in general.

New methods for the Preparation of Nitrosyl Chloride

A pure sample of nitrosyl chloride has been prepared either by reaction of phosphorus trichloride with concentrated nitric acid or by reaction of phosphorus trichloride with sodium nitrate in presence of water. The nitrosyl chloride gas has been characterized by i.r. spectral data and elemental analysis.

Practical Criterion for Universal Laws and Practical Methods for Construction of Co-variance Sets

给出相对论力学中普遍定律的实用判别法和协变集的实用构造法,还给出实现非普遍定律的“可导出性”的一种实用方法．

Advances in methods for determining fecundity: application of the new methods to some marine fishes

Estimation of individual egg production (realized fecundity) is a key step either to understand the stock and recruit relationship or to carry out fisheries-independent assessment of spawning stock biomass using egg production methods. Many fish are highly fecund and their ovaries may weigh over a kilogram; therefore the work time can be consuming and require large quantities of toxic fixative. Recently it has been shown for Atlantic cod (Gadus morhua) that image analysis can automate fecundity determination using a power equation that links follicles per gram ovary to the mean vitellogenic follicular diameter (the autodiametric method). In this article we demonstrate the precision of the autodiametric method applied to a range of species with different spawning strategies during maturation and spawning. A new method using a solid displacement pipette to remove quantitative fecundity samples (25, 50, 100, and 200 milligram [mg]) is evaluated, as are the underlying assumptions to effectively fix and subsample the ovary. Finally, we demonstrate the interpretation of dispersed formaldehyde-fixed ovarian samples (whole mounts) to assess the presence of atretic and postovulatory follicles to replace labor intensive histology. These results can be used to estimate down regulation (production of atretic follicles) of fecundity during maturation.

Comparative study of vision tracking methods for tracking of construction site resources

Vision tracking has significant potential for tracking resources on large scale, congested construction sites, where a small number of cameras strategically placed around the site could replace hundreds of tracking tags. The correlation of vision tracking 2D positions from multiple views can provide the 3D position. However, there are many 2D vision trackers available in the literature, and little information is available on which one is most effective for construction applications. In this paper, a comparative study of various vision tracker categories is carried out, to identify which one is most effective in tracking construction resources. Testing parameters for evaluating categories of trackers are identified, and benefits and limitations of each category are presented. The most promising trackers are tested using a database of construction operations videos. The results indicate the effectiveness of each tracker in relation to each parameter of the test, and the most suitable tracker needed to research effective 3D vision trackers of construction resources.

Comparison of manual and user guided methodologies for the classification and retrieval of construction site images

The amount of original imaging information produced yearly during the last decade has experienced a tremendous growth in all industries due to the technological breakthroughs in digital imaging and electronic storage capabilities. This trend is affecting the construction industry as well, where digital cameras and image databases are gradually replacing traditional photography. Owners demand complete site photograph logs and engineers store thousands of images for each project to use in a number of construction management tasks like monitoring an activity's progress and keeping evidence of the "as built" in case any disputes arise. So far, retrieval methodologies are done manually with the user being responsible for imaging classification according to specific rules that serve a limited number of construction management tasks. New methods that, with the guidance of the user, can automatically classify and retrieve construction site images are being developed and promise to remove the heavy burden of manually indexing images. In this paper, both the existing methods and a novel image retrieval method developed by the authors for the classification and retrieval of construction site images are described and compared. Specifically a number of examples are deployed in order to present their advantages and limitations. The results from this comparison demonstrates that the content based image retrieval method developed by the authors can reduce the overall time spent for the classification and retrieval of construction images while providing the user with the flexibility to retrieve images according different classification schemes.

Content Based Integration of Construction Site Images in AEC/FM Model Based Systems

The Architecture, Engineering, Construction and Facilities Management (AEC/FM) industry is rapidly becoming a multidisciplinary, multinational and multi-billion dollar economy, involving large numbers of actors working concurrently at different locations and using heterogeneous software and hardware technologies. Since the beginning of the last decade, a great deal of effort has been spent within the field of construction IT in order to integrate data and information from most computer tools used to carry out engineering projects. For this purpose, a number of integration models have been developed, like web-centric systems and construction project modeling, a useful approach in representing construction projects and integrating data from various civil engineering applications. In the modern, distributed and dynamic construction environment it is important to retrieve and exchange information from different sources and in different data formats in order to improve the processes supported by these systems. Previous research demonstrated that a major hurdle in AEC/FM data integration in such systems is caused by its variety of data types and that a significant part of the data is stored in semi-structured or unstructured formats. Therefore, new integrative approaches are needed to handle non-structured data types like images and text files. This research is focused on the integration of construction site images. These images are a significant part of the construction documentation with thousands stored in site photographs logs of large scale projects. However, locating and identifying such data needed for the important decision making processes is a very hard and time-consuming task, while so far, there are no automated methods for associating them with other related objects. Therefore, automated methods for the integration of construction images are important for construction information management. During this research, processes for retrieval, classification, and integration of construction images in AEC/FM model based systems have been explored. Specifically, a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval have been deployed in order to develop a methodology for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks.