A computational approach to the reconstruction of surface geometry from early temple superstructures

Recovering the control or implicit geometry underlying temple architecture requires bringing together fragments of evidence from field measurements, relating these to mathematical and geometric descriptions in canonical texts and proposing "best-fit" constructive models. While scholars in the field have traditionally used manual methods, the innovative application of niche computational techniques can help extend the study of artefact geometry. This paper demonstrates the application of a hybrid computational approach to the problem of recovering the surface geometry of early temple superstructures. The approach combines field measurements of temples, close-range architectural photogrammetry, rule-based generation and parametric modelling. The computing of surface geometry comprises a rule-based global model governing the overall form of the superstructure, several local models for individual motifs using photogrammetry and an intermediate geometry model that combines the two. To explain the technique and the different models, the paper examines an illustrative example of surface geometry reconstruction based on studies undertaken on a tenth century stone superstructure from western India. The example demonstrates that a combination of computational methods yields sophisticated models of the constructive geometry underlying temple form and that these digital artefacts can form the basis for in depth comparative analysis of temples, arising out of similar techniques, spread over geography, culture and time.

Analysis of stakeholder concerns with a view to avoid organisational conflict in B2B systems

In recent years there has been a remarkable increase in information exchange between organizations due to changes in market structures and new forms of business relationships. The increase in the volume of business-to-business (B2B) transactions has contributed significantly to the expanding need for electronic systems that could effectively support communication between collaborating organizations. Examples of such collaborating systems include those that offer various types of business-to-business services, e.g. electronic commerce, electronic procurement systems, electronic links between legacy systems, or outsourced systems providing data processing services via electronic media. Development and running of B2B electronic systems has not been problem free. One of the most intractable issues found in B2B systems is the prevalence of inter-organisational conflict reported to exist and persists between the participants of interorganisational electronic networks. There have been very few attempts, however, to prescribe any practical method of detecting the antecedents of such conflict early in B2B development to facilitate smooth construction and the subsequent operation of B2B services. The research reported in this paper focuses on the identification and analysis of antecedent conflict in a joint process involving different organizations in a B2B venture. The proposed method involves identification of domain stakeholders, capturing and packaging their views and concerns into a reusable form, and the application of captured domain experience in B2B systems development. The concepts and methods introduced in this paper have been illustrated with examples drawn from our study of six web-enabled payroll systems.

A matrix-based model for web page community construction and more

The rapid development of network technologies has made the web a huge information source with its own characteristics. In most cases, traditional database-based technologies are no longer suitable for web information processing and management. For effectively processing and managing web information, it is necessary to reveal intrinsic relationships/structures among concerned web information objects such as web pages. In this work, a set of web pages that have their intrinsic relationships is called a web page community. This paper proposes a matrix-based model to describe relationships among concerned web pages. Based on this model, intrinsic relationships among pages could be revealed, and in turn a web page community could be constructed. The issues that are related to the application of the model are deeply investigated and studied. The concepts of community and intrinsic relationships, as well as the proposed matrix-based model, are then extended to other application areas such as biological data processing. Some application cases of the model in a broad range of areas are presented, demonstrating the potentials of this matrix-based model.

Teaching practices for effective cooperative learning in an online learning environment (OLE)

As a teaching practice the application of cooperative learning in tertiary education can present unique challenges for both the practitioner and her students. Mastering this teaching approach requires careful planning, design and implementation for effective deployment in a face-to-face setting. In this setting the success of the cooperative learning approach has been demonstrated. The complexity is significantly increased by additional variables such as the selection and application of technological teaching tools and the change in nature of existing variables including awareness of students' social and communication skills when applying this practice in an Online Learning Environment (OLE). In addition student acceptance of this e-learning approach to learning also needs to be carefully considered. The practitioner must be aware of these factors and have suitable methods in place to support collaboration and interaction between student groups to ensure the ultimate goal with regard to students' learning is achieved. This paper considers how cooperative learning can be combined effectively with these variables and factors of an OLE, and begins with the presentation of a conceptual framework to represent this relationship as a constructive teaching practice. It is anticipated that the conceptual framework would be applied by other practitioners to facilitate cooperative teaching within their OLE. To demonstrate the validity of the framework a case scenario is provided using an Information Technology (IT) undergraduate unit named 'IT Practice'. This is a wholly online unit where extensive participation by the students within small groups is a core requirement. The paper demonstrates the themes of designing curriculum and assessment, as well as flexible teaching strategies for learner diversity but primarily concentrates on managing an effective OLE; that is managing small groups in an online teaching environment.

Web communities analysis and construction

Yanchun Zhang and his co-authors explain how to construct and analyse Web communities based on information like Web document contents, hyperlinks, or user access logs. Their approaches combine results from Web search algorithms, Web clustering methods, and Web usage mining. They also detail the necessary preliminaries needed to understand the algorithms presented, and they discuss several successful existing applications. Researchers and students in information retrieval and Web search find in this all the necessary basics and methods to create and understand Web communities. Professionals developing Web applications will additionally benefit from the samples presented for their own designs and implementations

Distributed network systems : from concepts to implementations

"This textbook covers both theoretical and practical aspects of distributed computing. It describes the client-server model for developing distributed network systems, the communication paradigms used in a distributed network system, and the principles of reliability and security in the design of distributed network systems." "This book is suitable for self-study or for use in classes. Most parts of the book have been used by the authors in their teaching of various topics including distributed systems, computer networks, and distributed database systems. This book can also serve as an invaluable guide for computing professionals in their work for the design and implementation of distributed network systems."

Optimal lag-length choice in stable and unstable VAR models under situations of homoscedasticity and ARCH

The performance of different information criteria - namely Akaike, corrected Akaike (AICC), Schwarz-Bayesian (SBC), and Hannan-Quinn - is investigated so as to choose the optimal lag length in stable and unstable vector autoregressive (VAR) models both when autoregressive conditional heteroscedasticity (ARCH) is present and when it is not. The investigation covers both large and small sample sizes. The Monte Carlo simulation results show that SBC has relatively better performance in lag-choice accuracy in many situations. It is also generally the least sensitive to ARCH regardless of stability or instability of the VAR model, especially in large sample sizes. These appealing properties of SBC make it the optimal criterion for choosing lag length in many situations, especially in the case of financial data, which are usually characterized by occasional periods of high volatility. SBC also has the best forecasting abilities in the majority of situations in which we vary sample size, stability, variance structure (ARCH or not), and forecast horizon (one period or five). frequently, AICC also has good lag-choosing and forecasting properties. However, when ARCH is present, the five-period forecast performance of all criteria in all situations worsens.

A scalable and extensible segment-event-object-based sports video retrieval system

Sport video data is growing rapidly as a result of the maturing digital technologies that support digital video capture, faster data processing, and large storage. However, (1) semi-automatic content extraction and annotation, (2) scalable indexing model, and (3) effective retrieval and browsing, still pose the most challenging problems for maximizing the usage of large video databases. This article will present the findings from a comprehensive work that proposes a scalable and extensible sports video retrieval system with two major contributions in the area of sports video indexing and retrieval. The first contribution is a new sports video indexing model that utilizes semi-schema-based indexing scheme on top of an Object-Relationship approach. This indexing model is scalable and extensible as it enables gradual index construction which is supported by ongoing development of future content extraction algorithms. The second contribution is a set of novel queries which are based on XQuery to generate dynamic and user-oriented summaries and event structures. The proposed sports video retrieval system has been fully implemented and populated with soccer, tennis, swimming, and diving video. The system has been evaluated against 20 users to demonstrate and confirm its feasibility and benefits. The experimental sports genres were specifically selected to represent the four main categories of sports domain: period-, set-point-, time (race)-, and performance-based sports. Thus, the proposed system should be generic and robust for all types of sports.

Multifractality and long-range dependence of asset returns: the scaling behavior of the Markov-switching multifractal model with lognormal volatility components

In this paper, we consider daily financial data from various sources (stock market indices, foreign exchange rates and bonds) and analyze their multiscaling properties by estimating the parameters of a Markov-switching multifractal (MSM) model with Lognormal volatility components. In order to see how well estimated models capture the temporal dependency of the empirical data, we estimate and compare (generalized) Hurst exponents for both empirical data and simulated MSM models. In general, the Lognormal MSM models generate "apparent" long memory in good agreement with empirical scaling provided that one uses sufficiently many volatility components. In comparison with a Binomial MSM specification [11], results are almost identical. This suggests that a parsimonious discrete specification is flexible enough and the gain from adopting the continuous Lognormal distribution is very limited.

TLAStat+ + Version 1

TLAStat+ is a powerful but easy to use statistics software package.It is an add-in for statistics to be used in conjunction with Microsoft Excel. It provides extra calculation, graph, and help features for statistical data analysis. TLAStat+ is designed for teaching introductory-intermediate courses in statistics. It runs on PCs in various versions of Excel and has powerful data handling capabilities.