Implementation of the CDM model to the analisys of the hotel sector

The main aim of this study was to determine the impact of innovation on productivity in service sector companies — especially those in the hospitality sector — that value the reduction of environmental impact as relevant to the innovation process. We used a structural analysis model based on the one developed by Crépon, Duguet, and Mairesse (1998). This model is known as the CDM model (an acronym of the authors’ surnames). These authors developed seminal studies in the field of the relationships between innovation and productivity (see Griliches 1979; Pakes and Grilliches 1980). The main advantage of the CDM model is its ability to integrate the process of innovation and business productivity from an empirical perspective.

On feasibility of regional frequency-based emergency control plans

Decentralized and regional load-frequency control of power systems operating in normal and near-normal conditions has been well studied; and several analysis/synthesis approaches have been developed during the last few decades. However in contingency and off-normal conditions, the existing emergency control plans, such as under-frequency load shedding, are usually applied in a centralized structure using a different analysis model. This paper discusses the feasibility of using frequency-based emergency control schemes based on tie-line measurements and local information available within a control area. The conventional load-frequency control model is generalized by considering the dynamics of emergency control/protection schemes and an analytic approach to analyze the regional frequency response under normal and emergency conditions is presented.

African Indigeneity

The current argument is that there exist no indigenous people in Africa because all Africans are indigenous. The obverse considers those Africans who have not been touched by colonialism and lost their traditional cultures commensurate with attachments to the lands or a distinguishable traditional lifestyle to be indigenous. This paper argues in favor of the latter. For example, modernism, materialism, ex-colonial socio-cultural impacts (as in the remnants of European legal structures, and cultural scarring), globalization, and technology are international social homogenizers. People who live in this telos and do not participate in a distinct traditional culture that has been attached to the land for centuries are not indigenous. It is argued that this cultural divergence between modern and traditional is the major identifying point to settle the indigenous-non indigenous African debate. Finally, the paper looks at inclusive development, how this helps to distinguish African indigeneity, and provides a new political analysis model for quantifying inclusivity.

Improving automatic speaker verification using SVM techniques

Automatic recognition of people is an active field of research with important forensic and security applications. In these applications, it is not always possible for the subject to be in close proximity to the system. Voice represents a human behavioural trait which can be used to recognise people in such situations. Automatic Speaker Verification (ASV) is the process of verifying a persons identity through the analysis of their speech and enables recognition of a subject at a distance over a telephone channel { wired or wireless. A significant amount of research has focussed on the application of Gaussian mixture model (GMM) techniques to speaker verification systems providing state-of-the-art performance. GMM's are a type of generative classifier trained to model the probability distribution of the features used to represent a speaker. Recently introduced to the field of ASV research is the support vector machine (SVM). An SVM is a discriminative classifier requiring examples from both positive and negative classes to train a speaker model. The SVM is based on margin maximisation whereby a hyperplane attempts to separate classes in a high dimensional space. SVMs applied to the task of speaker verification have shown high potential, particularly when used to complement current GMM-based techniques in hybrid systems. This work aims to improve the performance of ASV systems using novel and innovative SVM-based techniques. Research was divided into three main themes: session variability compensation for SVMs; unsupervised model adaptation; and impostor dataset selection. The first theme investigated the differences between the GMM and SVM domains for the modelling of session variability | an aspect crucial for robust speaker verification. Techniques developed to improve the robustness of GMMbased classification were shown to bring about similar benefits to discriminative SVM classification through their integration in the hybrid GMM mean supervector SVM classifier. Further, the domains for the modelling of session variation were contrasted to find a number of common factors, however, the SVM-domain consistently provided marginally better session variation compensation. Minimal complementary information was found between the techniques due to the similarities in how they achieved their objectives. The second theme saw the proposal of a novel model for the purpose of session variation compensation in ASV systems. Continuous progressive model adaptation attempts to improve speaker models by retraining them after exploiting all encountered test utterances during normal use of the system. The introduction of the weight-based factor analysis model provided significant performance improvements of over 60% in an unsupervised scenario. SVM-based classification was then integrated into the progressive system providing further benefits in performance over the GMM counterpart. Analysis demonstrated that SVMs also hold several beneficial characteristics to the task of unsupervised model adaptation prompting further research in the area. In pursuing the final theme, an innovative background dataset selection technique was developed. This technique selects the most appropriate subset of examples from a large and diverse set of candidate impostor observations for use as the SVM background by exploiting the SVM training process. This selection was performed on a per-observation basis so as to overcome the shortcoming of the traditional heuristic-based approach to dataset selection. Results demonstrate the approach to provide performance improvements over both the use of the complete candidate dataset and the best heuristically-selected dataset whilst being only a fraction of the size. The refined dataset was also shown to generalise well to unseen corpora and be highly applicable to the selection of impostor cohorts required in alternate techniques for speaker verification.

Establishing indigeneity in African pluralities using PRO169 parameters and a case study for measuring their inclusivity

The concept of the indigenous person or group in Africa is a contentious one. The current argument is that there exist no indigenous people in Africa because all Africans are indigenous. The obverse considers those Africans who have not been touched by colonialism and lost their traditional cultures commensurate with attachments to the lands or a distinguishable traditional lifestyle to be indigenous. This paper argues in favor of the latter. People who live in the global telos and do not participate in a distinct traditional culture that has been attached to the land for centuries are not indigenous. It is argued that this cultural divergence between modern and traditional is the major identifying point to settle the indigenous-non indigenous African debate. Finally, the paper looks at inclusive development and provides a new political analysis model for quantifying inclusivity so as to measure the inclusivity of indigenous peoples.

A Two-stage information filtering based on rough decision rule and pattern mining

Information Overload and Mismatch are two fundamental problems affecting the effectiveness of information filtering systems. Even though both term-based and patternbased approaches have been proposed to address the problems of overload and mismatch, neither of these approaches alone can provide a satisfactory solution to address these problems. This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern-based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experimental results based on the RCV1 corpus show that the proposed twostage filtering model significantly outperforms the both termbased and pattern-based information filtering models.

Rough sets based reasoning and pattern mining for a two-stage information filtering system

This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern- based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experiments have been conducted to compare the proposed two-stage filtering (T-SM) model with other possible "term-based + pattern-based" or "term-based + term-based" IF models. The results based on the RCV1 corpus show that the T-SM model significantly outperforms other types of "two-stage" IF models.

Digital human modelling for vehicle design and manufacturing

Digital human modelling (DHM) has today matured from research into industrial application. In the automotive domain, DHM has become a commonly used tool in virtual prototyping and human-centred product design. While this generation of DHM supports the ergonomic evaluation of new vehicle design during early design stages of the product, by modelling anthropometry, posture, motion or predicting discomfort, the future of DHM will be dominated by CAE methods, realistic 3D design, and musculoskeletal and soft tissue modelling down to the micro-scale of molecular activity within single muscle fibres. As a driving force for DHM development, the automotive industry has traditionally used human models in the manufacturing sector (production ergonomics, e.g. assembly) and the engineering sector (product ergonomics, e.g. safety, packaging). In product ergonomics applications, DHM share many common characteristics, creating a unique subset of DHM. These models are optimised for a seated posture, interface to a vehicle seat through standardised methods and provide linkages to vehicle controls. As a tool, they need to interface with other analytic instruments and integrate into complex CAD/CAE environments. Important aspects of current DHM research are functional analysis, model integration and task simulation. Digital (virtual, analytic) prototypes or digital mock-ups (DMU) provide expanded support for testing and verification and consider task-dependent performance and motion. Beyond rigid body mechanics, soft tissue modelling is evolving to become standard in future DHM. When addressing advanced issues beyond the physical domain, for example anthropometry and biomechanics, modelling of human behaviours and skills is also integrated into DHM. Latest developments include a more comprehensive approach through implementing perceptual, cognitive and performance models, representing human behaviour on a non-physiologic level. Through integration of algorithms from the artificial intelligence domain, a vision of the virtual human is emerging.

Innovative damage assessment of steel truss bridges using modal strain energy correlation

As a part of vital infrastructure and transportation network, bridge structures must function safely at all times. Bridges are designed to have a long life span. At any point in time, however, some bridges are aged. The ageing of bridge structures, given the rapidly growing demand of heavy and fast inter-city passages and continuous increase of freight transportation, would require diligence on bridge owners to ensure that the infrastructure is healthy at reasonable cost. In recent decades, a new technique, structural health monitoring (SHM), has emerged to meet this challenge. In this new engineering discipline, structural modal identification and damage detection have formed a vital component. Witnessed by an increasing number of publications is that the change in vibration characteristics is widely and deeply investigated to assess structural damage. Although a number of publications have addressed the feasibility of various methods through experimental verifications, few of them have focused on steel truss bridges. Finding a feasible vibration-based damage indicator for steel truss bridges and solving the difficulties in practical modal identification to support damage detection motivated this research project. This research was to derive an innovative method to assess structural damage in steel truss bridges. First, it proposed a new damage indicator that relies on optimising the correlation between theoretical and measured modal strain energy. The optimisation is powered by a newly proposed multilayer genetic algorithm. In addition, a selection criterion for damage-sensitive modes has been studied to achieve more efficient and accurate damage detection results. Second, in order to support the proposed damage indicator, the research studied the applications of two state-of-the-art modal identification techniques by considering some practical difficulties: the limited instrumentation, the influence of environmental noise, the difficulties in finite element model updating, and the data selection problem in the output-only modal identification methods. The numerical (by a planer truss model) and experimental (by a laboratory through truss bridge) verifications have proved the effectiveness and feasibility of the proposed damage detection scheme. The modal strain energy-based indicator was found to be sensitive to the damage in steel truss bridges with incomplete measurement. It has shown the damage indicator's potential in practical applications of steel truss bridges. Lastly, the achievement and limitation of this study, and lessons learnt from the modal analysis have been summarised.

Reliable and valid survey design for structural equation modelling

My quantitative study asks how Chinese Australians’ “Chineseness” and their various resources influence their Chinese language proficiency, using online survey and snowball sampling. ‘Operationalization’ is a challenging process which ensures that the survey design talks back to the informing theory and forwards to the analysis model. It requires the attention to two core methodological concerns, namely ‘validity’ and ‘reliability’. Construction of a high-quality questionnaire is critical to the achievement of valid and reliable operationalization. A series of strategies were chosen to ensure the quality of the questions, and thus the eventual data. These strategies enable the use of structural equation modelling to examine how well the data fits the theoretical framework, which was constructed in light of Bourdieu’s theory of habitus, capital and field.

What factors influence nurses’ assessment practices? Development of the Barriers to Nurses’ use of Physical Assessment Scale

Aim To develop and psychometrically test the Barriers to Nurses’ use of Physical Assessment Scale. Background There is growing evidence of failure to recognise hospitalised patients at risk of clinical deterioration, in part due to inadequate physical assessment by nurses. Yet, little is known about the barriers to nurses’ use of physical assessment in the acute hospital setting and no validated scales have been published. Design Instrument development study. Method Scale development was based on a comprehensive literature review, focus groups, expert review and psychometric evaluation. The scale was administered to 434 acute care registered nurses working at a large Australian teaching hospital between June and July 2013. Psychometric analysis included factor analysis, model fit statistics and reliability testing. Results The final scale was reduced to 38 items representing seven factors, together accounting for 57.7% of the variance: (1) reliance on others and technology, (2) lack of time and interruptions, (3) ward culture, (4) lack of confidence, (5) lack of nursing role models, (6) lack of influence on patient care, and; (7) specialty area. Internal reliability ranged from .70 to .86. Conclusion Findings provide initial evidence for the validity and reliability of the Barriers to Nurses’ use of Physical Assessment Scale and point to the importance of understanding the organisational determinants of nurses’ assessment practices. The new scale has potential clinical and research applications to support nursing assessment in acute care settings.

JK1 (FAM134B) represses cell migration in colon cancer : a functional study of a novel gene

Background JK1 is a novel cancer-related gene with unknown functional role in carcinogenesis. The aim of this study is to investigate the role of JK1 gene in carcinogenesis in an in vitro cell proliferation and migration analysis model. Methods Small hairpin RNAs (shRNA) were designed to knock-down JK1 expression in colon cancer cell line (SW480) using transduction ready lentiviral particles. Cell proliferation and cell migration assays were performed on multiple extracellular matrices to investigate the cellular effects of JK1 in colon cancer cells. A non-cancer colonic epithelial cell line (FHC) was used to compare the expression of JK1 in cancer cell line. Results JK1 knock-down did not affect cellular proliferation or survival in colon cancer. However, the manipulation increased cancer cell migration rates on collagen and fibronectin substrates. Conclusions JK1 was shown for the first time to have a functional role in the pathogenesis of colon cancer. The results imply that JK1 represses the capacity of cancer cells to migrate within their tissue. They also concurred with the previous findings of JK1 activity correlations with clinical and pathological features in colon cancer. The capacity may have utility as a means to prevent cancer cells forming metastases.

From Iron Horse to Rauta-airot - a Semiotic View on the Domestication of Metaphors in Literary Translation

The thesis concentrates on two questions: the translation of metaphors in literary texts, and the use of semiotic models and tools in translation studies. The aim of the thesis is to present a semiotic, text based model designed to ease the translation of metaphors and to analyze translated metaphors. In the translation of metaphors I will concentrate on the central problem of metaphor translations: in addition to its denotation and connotation, a single metaphor may contain numerous culture or genre specific meanings. How can a translator ensure the translation of all meanings relevant to the text as a whole? I will approach the question from two directions. Umberto Eco's holistic text analysis model provides an opportunity to concentrate on the problematic nature of metaphor translation from the level of a text as a specific entity, while George Lakoff's and Mark Johnson's metaphor research makes it possible to approach the question from the level of individual metaphors. On the semiotic side, the model utilizes Eero Tarasti's existential semiotics supported by Algirdas Greimas' actant model and Yuri Lotman's theory of cultural semiotics. In the model introduced in the thesis, individual texts are deconstructed through Eco's model into elements. The textual roles and features of these elements are distilled further through Tarasti's model into their coexistent meaning levels. The priorization and analysis of these meaning levels provide an opportunity to consider the contents and significance of specific metaphors in relation to the needs of the text as a whole. As example texts, I will use Motörhead's hard rock classic Iron Horse/Born to Lose and its translation into Rauta-airot by Viikate. I will use the introduced model to analyze the metaphors in the source and target texts, and to consider the transfer of culture specific elements between the languages and cultural borders. In addition, I will use the analysis process to examine the validity of the model introduced in the thesis.

On linear order and computation : The expressiveness of interactive computations on linear orders and computations indexed by ordinals

We solve the Dynamic Ehrenfeucht-Fra\"iss\'e Game on linear orders for both players, yielding a normal form for quantifier-rank equivalence classes of linear orders in first-order logic, infinitary logic, and generalized-infinitary logics with linearly ordered clocks. We show that Scott Sentences can be manipulated quickly, classified into local information, and consistency can be decided effectively in the length of the Scott Sentence. We describe a finite set of linked automata moving continuously on a linear order. Running them on ordinals, we compute the ordinal truth predicate and compute truth in the constructible universe of set-theory. Among the corollaries are a study of semi-models as efficient database of both model-theoretic and formulaic information, and a new proof of the atomicity of the Boolean algebra of sentences consistent with the theory of linear order -- i.e., that the finitely axiomatized theories of linear order are dense.

Barrett's Esophagus and Associated Adenocarcinoma : studies on pathogenesis, clinical staging and cost-utility of cancer treatment

Esophageal and gastroesophageal junction (GEJ) adenocarcinoma is rapidly increasing disease with a pathophysiology connected to oxidative stress. Exact pre-treatment clinical staging is essential for optimal care of this lethal malignancy. The cost-effectiviness of treatment is increasingly important. We measured oxidative metabolism in the distal and proximal esophagus by myeloperoxidase activity (MPA), glutathione content (GSH), and superoxide dismutase (SOD) in 20 patients operated on with Nissen fundoplication and 9 controls during a 4-year follow-up. Further, we assessed the oxidative damage of DNA by 8-hydroxydeoxyguanosine (8-OHdG) in esophageal samples of subjects (13 Barrett s metaplasia, 6 Barrett s esophagus with high-grade dysplasia, 18 adenocarcinoma of the distal esophagus/GEJ, and 14 normal controls). We estimated the accuracy (42 patients) and preoperative prognostic value (55 patients) of PET compared with computed tomography (CT) and endoscopic ultrasound (EUS) in patients with adenocarcinoma of the esophagus/GEJ. Finally, we clarified the specialty-related costs and the utility of either radical (30 patients) or palliative (23 patients) treatment of esophageal/GEJ carcinoma by the 15 D health-related quality-of-life (HRQoL) questionnaire and the survival rate. The cost-utility of radical treatment of esophageal/GEJ carcinoma was investigated using a decision tree analysis model comparing radical, palliative, and hypothetical new treatment. We found elevated oxidative stress ( measured by MPA) and decreased antioxidant defense (measured by GSH) after antireflux surgery. This indicates that antireflux surgery is not a perfect solution for oxidative stress of the esophageal mucosa. Elevated oxidative stress in turn may partly explain why adenocarcinoma of the distal esophagus is found even after successful fundoplication. In GERD patients, proximal esophageal mucosal anti-oxidative defense seems to be defective before and even years after successful antireflux surgery. In addition, antireflux surgery apparently does not change the level of oxidative stress in the proximal esophagus, suggesting that defective mucosal anti-oxidative capacity plays a role in development of oxidative damage to the esophageal mucosa in GERD. In the malignant transformation of Barrett s esophagus an important component appears to be oxidative stress. DNA damage may be mediated by 8-OHdG, which we found to be increased in Barrett s epithelium and in high-grade dysplasia as well as in adenocarcinoma of the esophagus/GEJ compared with controls. The entire esophagus of Barrett s patients suffers from increased oxidative stress ( measured by 8-OhdG). PET is a useful tool in the staging and prognostication of adenocarcinoma of the esophagus/GEJ detecting organ metastases better than CT, although its accuracy in staging of paratumoral and distant lymph nodes is limited. Radical surgery for esophageal/GEJ carcinoma provides the greatest benefit in terms of survival, and its cost-utility appears to be the best of currently available treatments.