Tuning the valence of the cerium center in (Na)phthalocyaninato and porphyrinato cerium double-deckers by changing the nature of the tetrapyrrole ligands

A series of 7 cerium double-decker complexes with various tetrapyrrole ligands including porphyrinates, phthalocyaninates, and 2,3-naphthalocyaninates have been prepared by previously described methodologies and characterized with elemental analysis and a range of spectroscopic methods. The molecular structures of two heteroleptic \[(na)phthalocyaninato](porphyrinato) complexes have also been determined by X-ray diffraction analysis which exhibit a slightly distorted square antiprismatic geometry with two domed ligands. Having a range of tetrapyrrole ligands with very different electronic properties, these compounds have been systematically investigated for the effects of ligands on the valence of the cerium center. On the basis of the spectroscopic (UV−vis, near-IR, IR, and Raman), electrochemical, and structural data of these compounds and compared with those of the other rare earth(III) counterparts reported earlier, it has been found that the cerium center adopts an intermediate valence in these complexes. It assumes a virtually trivalent state in cerium bis(tetra-tert-butylnaphthalocyaninate) as a result of the two electron rich naphthalocyaninato ligands, which facilitate the delocalization of electron from the ligands to the metal center. For the rest of the cerium double-deckers, the cerium center is predominantly tetravalent. The valences (3.59−3.68) have been quantified according to their LIII-edge X-ray absorption near-edge structure (XANES) profiles.

Study on the method of freeway incident detection using wireless positioning terminal

Improving the performance of a incident detection system was essential to minimize the effect of incidents. A new method of incident detection was brought forward in this paper based on an in-car terminal which consisted of GPS module, GSM module and control module as well as some optional parts such as airbag sensors, mobile phone positioning system (MPPS) module, etc. When a driver or vehicle discovered the freeway incident and initiated an alarm report the incident location information located by GPS, MPPS or both would be automatically send to a transport management center (TMC), then the TMC would confirm the accident with a closed-circuit television (CCTV) or other approaches. In this method, detection rate (DR), time to detect (TTD) and false alarm rate (FAR) were more important performance targets. Finally, some feasible means such as management mode, education mode and suitable accident confirming approaches had been put forward to improve these targets.

Silylation of layered double hydroxides via a calcination−rehydration route

Silylated layered double hydroxides (LDHs) were synthesized through a surfactant-free method involving an in situ condensation of silane with the surface hydroxyl group of LDHs during its reconstruction in carbonate solution. X-ray diffraction (XRD) patterns showed the silylation reaction occurred on the external surfaces of LDHs layers. The successful silylation was evidenced by 29Si cross-polarization magic-angle spinning nuclear magnetic resonance (29Si CP/MAS NMR) spectroscopy, attenuated total reflection Fourier transform infrared (ATR FTIR) spectroscopy, and infrared emission spectroscopy (IES). The ribbon shaped crystallites with a “rodlike” aggregation were observed through transmission electron microscopy (TEM) images. The aggregation was explained by the T2 and T3 types of linkage between adjacent silane molecules as indicated in the 29Si NMR spectrum. In addition, the silylated products show high thermal stability by maintained Si related bands even when the temperature was increased to 1000 °C as observed in IES spectra.

Personalised ontology learning and mining for web information gathering

Over the last decade, the rapid growth and adoption of the World Wide Web has further exacerbated user needs for e±cient mechanisms for information and knowledge location, selection, and retrieval. How to gather useful and meaningful information from the Web becomes challenging to users. The capture of user information needs is key to delivering users' desired information, and user pro¯les can help to capture information needs. However, e®ectively acquiring user pro¯les is di±cult. It is argued that if user background knowledge can be speci¯ed by ontolo- gies, more accurate user pro¯les can be acquired and thus information needs can be captured e®ectively. Web users implicitly possess concept models that are obtained from their experience and education, and use the concept models in information gathering. Prior to this work, much research has attempted to use ontologies to specify user background knowledge and user concept models. However, these works have a drawback in that they cannot move beyond the subsumption of super - and sub-class structure to emphasising the speci¯c se- mantic relations in a single computational model. This has also been a challenge for years in the knowledge engineering community. Thus, using ontologies to represent user concept models and to acquire user pro¯les remains an unsolved problem in personalised Web information gathering and knowledge engineering. In this thesis, an ontology learning and mining model is proposed to acquire user pro¯les for personalised Web information gathering. The proposed compu- tational model emphasises the speci¯c is-a and part-of semantic relations in one computational model. The world knowledge and users' Local Instance Reposito- ries are used to attempt to discover and specify user background knowledge. From a world knowledge base, personalised ontologies are constructed by adopting au- tomatic or semi-automatic techniques to extract user interest concepts, focusing on user information needs. A multidimensional ontology mining method, Speci- ¯city and Exhaustivity, is also introduced in this thesis for analysing the user background knowledge discovered and speci¯ed in user personalised ontologies. The ontology learning and mining model is evaluated by comparing with human- based and state-of-the-art computational models in experiments, using a large, standard data set. The experimental results are promising for evaluation. The proposed ontology learning and mining model in this thesis helps to develop a better understanding of user pro¯le acquisition, thus providing better design of personalised Web information gathering systems. The contributions are increasingly signi¯cant, given both the rapid explosion of Web information in recent years and today's accessibility to the Internet and the full text world.

Effective pattern taxonomy mining in text documents

Many data mining techniques have been proposed for mining useful patterns in databases. However, how to effectively utilize discovered patterns is still an open research issue, especially in the domain of text mining. Most existing methods adopt term-based approaches. However, they all suffer from the problems of polysemy and synonymy. This paper presents an innovative technique, pattern taxonomy mining, to improve the effectiveness of using discovered patterns for finding useful information. Substantial experiments on RCV1 demonstrate that the proposed solution achieves encouraging performance.

Efficient and accurate retrieval of business process models through indexing

Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to manage large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business process model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective than developing them from scratch. As process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. Experiments are conducted to demonstrate that our proposal achieves a significant reduction in query evaluation time.

A framework for strategic infrastructure asset management

The concept of asset management is not a new but an evolving idea that has been attracting attention of many organisations operating and/or owning some kind of infrastructure assets. The term asset management have been used widely with fundamental differences in interpretation and usage. Regardless of the context of the usage of the term, asset management implies the process of optimising return by scrutinising performance and making key strategic decisions throughout all phases of an assets lifecycle (Sarfi and Tao, 2004). Hence, asset management is a philosophy and discipline through which organisations are enabled to more effectively deploy their resources to provide higher levels of customer service and reliability while balancing financial objectives. In Australia, asset management made its way into the public works in 1993 when the Australian Accounting Standard Board issued the Australian Accounting Standard 27 – AAS27. Standard AAS27 required government agencies to capitalise and depreciate assets rather than expense them against earnings. This development has indirectly forced organisations managing infrastructure assets to consider the useful life and cost effectiveness of asset investments. The Australian State Treasuries and the Australian National Audit Office was the first organisation to formalise the concepts and principles of asset management in Australia in which they defined asset management as “ a systematic, structured process covering the whole life of an asset”(Australian National Audit Office, 1996). This initiative led other Government bodies and industry sectors to develop, refine and apply the concept of asset management in the management of their respective infrastructure assets. Hence, it can be argued that the concept of asset management has emerged as a separate and recognised field of management during the late 1990s. In comparison to other disciplines such as construction, facilities, maintenance, project management, economics, finance, to name a few, asset management is a relatively new discipline and is clearly a contemporary topic. The primary contributors to the literature in asset management are largely government organisations and industry practitioners. These contributions take the form of guidelines and reports on the best practice of asset management. More recently, some of these best practices have been made to become a standard such as the PAS 55 (IAM, 2004, IAM, 2008b) in UK. As such, current literature in this field tends to lack well-grounded theories. To-date, while receiving relatively more interest and attention from empirical researchers, the advancement of this field, particularly in terms of the volume of academic and theoretical development is at best moderate. A plausible reason for the lack of advancement is that many researchers and practitioners are still unaware of, or unimpressed by, the contribution that asset management can make to the performance of infrastructure asset. This paper seeks to explore the practices of organisations that manage infrastructure assets to develop a framework of strategic infrastructure asset management processes. It will begin by examining the development of asset management. This is followed by the discussion on the method to be adopted for this paper. Next, is the discussion of the result form case studies. It first describes the goals of infrastructure asset management and how they can support the broader business goals. Following this, a set of core processes that can support the achievement of business goals are provided. These core processes are synthesised based on the practices of asset managers in the case study organisations.

Efficient querying of large process model repositories

Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to manage large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business process model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective and less error-prone than developing them from scratch. Since process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. To make our approach more applicable, we consider the semantic similarity between labels. Experiments are conducted to demonstrate that our approach is efficient.

Manipulating double-decker molecules at the liquid-solid interface

We have used a scanning tunneling microscope to manipulate heteroleptic phthalocyaninato, naphthalocyaninato, porphyrinato double-decker molecules at the liquid/solid interface between 1-phenyloctane solvent and graphite. We employed nano-grafting of phthalocyanines with eight octyl chains to place these molecules into a matrix of heteroleptic double-decker molecules; the overlayer structure is epitaxial on graphite. We have also used nano-grafting to place double-decker molecules in matrices of single-layer phthalocyanines with octyl chains. Rectangular scans with a scanning tunneling microscope at low bias voltage resulted in the removal of the adsorbed doubledecker molecular layer and substituted the double-decker molecules with bilayer-stacked phthalocyanines from phenyloctane solution. Single heteroleptic double-decker molecules with lutetium sandwiched between naphthalocyanine and octaethylporphyrin were decomposed with voltage pulses from the probe tip; the top octaethylporphyrin ligand was removed and the bottom naphthalocyanine ligand remained on the surface. A domain of decomposed molecules was formed within the double-decker molecular domain, and the boundary of the decomposed molecular domain self-cured to become rectangular. We demonstrated a molecular “sliding block puzzle” with cascades of double-decker molecules on the graphite surface.

Ontology-based specific and exhaustive user profiles for constraint information fusion for multi-agents

Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment.