i-Cobb - An innovative technique in spinal radiographic measurement

The measurement of Cobb angles from radiographs is routine practice in spinal clinics. The technique relies on the use and availability of specialist equipment such as a goniometer, cobbometer or protractor. The aim of this study was to validate the use of i-Phone (Apple Inc) combined with Tilt Meter Pro software as compared to a protractor in the measurement of Cobb angles. Between November 2008 and December 2008 20 patients were selected at random from the Paediatric Spine Research Groups Database. A power calculation was performed which indicated if n=240 measurements the study had a 96% chance of detecting a 5 degree difference between groups. All patients had idiopathic scoliosis with a range of curve types and severities. The study found the i-Phone combined with Tilt Meter Pro software offers a faster alternative to the traditional method of Cobb angle measurement. The use of i-Phone offers a more convenient way of measuring Cobb angles in the outpatient setting. The intra-observer repeatability of the iPhone is equivalent to the protractor in the measurement of Cobb angles.

Improving behaviour classification consistency: a technique from biological taxonomy

Quantitative behaviour analysis requires the classification of behaviour to produce the basic data. In practice, much of this work will be performed by multiple observers, and maximising inter-observer consistency is of particular importance. Another discipline where consistency in classification is vital is biological taxonomy. A classification tool of great utility, the binary key, is designed to simplify the classification decision process and ensure consistent identification of proper categories. We show how this same decision-making tool - the binary key - can be used to promote consistency in the classification of behaviour. The construction of a binary key also ensures that the categories in which behaviour is classified are complete and non-overlapping. We discuss the general principles of design of binary keys, and illustrate their construction and use with a practical example from education research.

Effective web service discovery using a combination of a semantic model and a data mining technique

With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding an appropriate Web service according to the requirement of the user is a challenge. This warrants the need to establish an effective and reliable process of Web service discovery. A considerable body of research has emerged to develop methods to improve the accuracy of Web service discovery to match the best service. The process of Web service discovery results in suggesting many individual services that partially fulfil the user’s interest. By considering the semantic relationships of words used in describing the services as well as the use of input and output parameters can lead to accurate Web service discovery. Appropriate linking of individual matched services should fully satisfy the requirements which the user is looking for. This research proposes to integrate a semantic model and a data mining technique to enhance the accuracy of Web service discovery. A novel three-phase Web service discovery methodology has been proposed. The first phase performs match-making to find semantically similar Web services for a user query. In order to perform semantic analysis on the content present in the Web service description language document, the support-based latent semantic kernel is constructed using an innovative concept of binning and merging on the large quantity of text documents covering diverse areas of domain of knowledge. The use of a generic latent semantic kernel constructed with a large number of terms helps to find the hidden meaning of the query terms which otherwise could not be found. Sometimes a single Web service is unable to fully satisfy the requirement of the user. In such cases, a composition of multiple inter-related Web services is presented to the user. The task of checking the possibility of linking multiple Web services is done in the second phase. Once the feasibility of linking Web services is checked, the objective is to provide the user with the best composition of Web services. In the link analysis phase, the Web services are modelled as nodes of a graph and an allpair shortest-path algorithm is applied to find the optimum path at the minimum cost for traversal. The third phase which is the system integration, integrates the results from the preceding two phases by using an original fusion algorithm in the fusion engine. Finally, the recommendation engine which is an integral part of the system integration phase makes the final recommendations including individual and composite Web services to the user. In order to evaluate the performance of the proposed method, extensive experimentation has been performed. Results of the proposed support-based semantic kernel method of Web service discovery are compared with the results of the standard keyword-based information-retrieval method and a clustering-based machine-learning method of Web service discovery. The proposed method outperforms both information-retrieval and machine-learning based methods. Experimental results and statistical analysis also show that the best Web services compositions are obtained by considering 10 to 15 Web services that are found in phase-I for linking. Empirical results also ascertain that the fusion engine boosts the accuracy of Web service discovery by combining the inputs from both the semantic analysis (phase-I) and the link analysis (phase-II) in a systematic fashion. Overall, the accuracy of Web service discovery with the proposed method shows a significant improvement over traditional discovery methods.

A bridging transition technique for the combination of meshfree method with finite element method in 2D solids and structures

For certain continuum problems, it is desirable and beneficial to combine two different methods together in order to exploit their advantages while evading their disadvantages. In this paper, a bridging transition algorithm is developed for the combination of the meshfree method (MM) with the finite element method (FEM). In this coupled method, the meshfree method is used in the sub-domain where the MM is required to obtain high accuracy, and the finite element method is employed in other sub-domains where FEM is required to improve the computational efficiency. The MM domain and the FEM domain are connected by a transition (bridging) region. A modified variational formulation and the Lagrange multiplier method are used to ensure the compatibility of displacements and their gradients. To improve the computational efficiency and reduce the meshing cost in the transition region, regularly distributed transition particles, which are independent of either the meshfree nodes or the FE nodes, can be inserted into the transition region. The newly developed coupled method is applied to the stress analysis of 2D solids and structures in order to investigate its’ performance and study parameters. Numerical results show that the present coupled method is convergent, accurate and stable. The coupled method has a promising potential for practical applications, because it can take advantages of both the meshfree method and FEM when overcome their shortcomings.

Organizational ambidexterity and corporate entrepreneurship : the differential effects on venturing, innovation and renewal processes

Most corporate entrepreneurship studies have focused on either innovation, venturing or strategic renewal making comparison between the antecedents of all three aspects of corporate entrepreneurship difficult. Moreover, studies on corporate entrepreneurship hardly address organizational antecedents, while simultaneously managing and organizing CE and mainstream activities has been seen as a major challenge for incumbent firms. Our findings show that organizational ambidexterity has strong and differential effects on venturing, innovation and renewal. We find, for example, that innovation is affected by horizontal integration, while strategic renewal is significantly influenced by integration on top management team level.

I-cobb - An innovative technique in spinal radiographic measurement

The measurement of Cobb angles on radiographs of patients with spinal deformities is routine practice in spinal clinics. The technique relies on the use and availability of specialist equipment such as a goniometer, cobbometer or protractor. The aim of this study was to validate the use of i-Phone (Apple Inc) combined with Tilt Meter Pro software as compared to a protractor in the measurement of Cobb angles. The i-Phone combined with Tilt Meter Pro software offers a faster alternative to the traditional method of Cobb angle measurement. The use of i-Phone offers a more convenient way of measuring Cobb angles in the outpatient setting. The intra-observer repeatability of the iPhone is equivalent to the protractor in the measurement of Cobb angles.

Constructive development of the solutions of linear equations in introductory ordinary differential equations

The solution of linear ordinary differential equations (ODEs) is commonly taught in first year undergraduate mathematics classrooms, but the understanding of the concept of a solution is not always grasped by students until much later. Recognising what it is to be a solution of a linear ODE and how to postulate such solutions, without resorting to tables of solutions, is an important skill for students to carry with them to advanced studies in mathematics. In this study we describe a teaching and learning strategy that replaces the traditional algorithmic, transmission presentation style for solving ODEs with a constructive, discovery based approach where students employ their existing skills as a framework for constructing the solutions of first and second order linear ODEs. We elaborate on how the strategy was implemented and discuss the resulting impact on a first year undergraduate class. Finally we propose further improvements to the strategy as well as suggesting other topics which could be taught in a similar manner.

The differential effects of organizational antecedents on dimensions of corporate entrepreneurship

This study seeks to further delineate how organizational antecedents differentially influence the three components of corporate entrepreneurship: innovation, venturing or strategic renewal. We argue that structural differentiation may help organizations to maintain multiple and often conflicting demands of entrepreneurial and mainstream activities. Taking a social capital perspective, our study further examines two contingencies in the form of informal integration mechanisms (i.e. connectedness and TMT social integration). Our findings show structural differentiation has a positive effect on all three components of corporate entrepreneurship, yet the effect is moderated by integration mechanisms. Interunit connectedness has a positive moderation effect regarding innovation and venturing, and TMT social integration has a negative moderation effect regarding strategic renewal. This reveals that innovation is influenced by informal integration mechanisms on the organizational level, strategic renewal on top management team level, while venturing is influenced by integration mechanisms on both levels.

Differential reporting and the effect on loan evaluations : an experimental study

This study utilises a mexed design laboratory experiment to test the impact of differential reporting on one group of external financial report users-lenders. The results indicate that the judgments of bank loan officers' assessment of the ability of a borrower to repay, are not significantly affected by differential reporting (in this case, presentation on non-GAAP financial reports compared to GAAP financial reports). However, bankers request additional information from borrowers when non-GAAP financial reports are presented.

Thermal transition properties of spagehetti measured by Differential Scanning Calorimetry (DSC) and Thermal Mechanical Compression Test (TMCT)

Glass transition temperature of spaghetti sample was measured by thermal and rheological methods as a function of water content.

A differential kinetic spectrophotometric method for determination of three sulphanilamide artificial sweeteners with the aid of chemometrics

A simple and sensitive spectrophotometric method for the simultaneous determination of acesulfame-K, sodium cyclamate and saccharin sodium sweeteners in foodstuff samples has been researched and developed. This analytical method relies on the different kinetic rates of the analytes in their oxidative reaction with KMnO4 to produce the green manganate product in an alkaline solution. As the kinetic rates of acesulfame-K, sodium cyclamate and saccharin sodium were similar and their kinetic data seriously overlapped, chemometrics methods, such as partial least squares (PLS), principal component regression (PCR) and classical least squares (CLS), were applied to resolve the kinetic data. The results showed that the PLS prediction model performed somewhat better. The proposed method was then applied for the determination of the three sweeteners in foodstuff samples, and the results compared well with those obtained by the reference HPLC method.

Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved Hough transform

Spatial information captured from optical remote sensors on board unmanned aerial vehicles (UAVs) has great potential in automatic surveillance of electrical infrastructure. For an automatic vision-based power line inspection system, detecting power lines from a cluttered background is one of the most important and challenging tasks. In this paper, a novel method is proposed, specifically for power line detection from aerial images. A pulse coupled neural filter is developed to remove background noise and generate an edge map prior to the Hough transform being employed to detect straight lines. An improved Hough transform is used by performing knowledge-based line clustering in Hough space to refine the detection results. The experiment on real image data captured from a UAV platform demonstrates that the proposed approach is effective for automatic power line detection.