Particle swarm optimization aided orthogonal forward regression for unified data modeling

We propose a unified data modeling approach that is equally applicable to supervised regression and classification applications, as well as to unsupervised probability density function estimation. A particle swarm optimization (PSO) aided orthogonal forward regression (OFR) algorithm based on leave-one-out (LOO) criteria is developed to construct parsimonious radial basis function (RBF) networks with tunable nodes. Each stage of the construction process determines the center vector and diagonal covariance matrix of one RBF node by minimizing the LOO statistics. For regression applications, the LOO criterion is chosen to be the LOO mean square error, while the LOO misclassification rate is adopted in two-class classification applications. By adopting the Parzen window estimate as the desired response, the unsupervised density estimation problem is transformed into a constrained regression problem. This PSO aided OFR algorithm for tunable-node RBF networks is capable of constructing very parsimonious RBF models that generalize well, and our analysis and experimental results demonstrate that the algorithm is computationally even simpler than the efficient regularization assisted orthogonal least square algorithm based on LOO criteria for selecting fixed-node RBF models. Another significant advantage of the proposed learning procedure is that it does not have learning hyperparameters that have to be tuned using costly cross validation. The effectiveness of the proposed PSO aided OFR construction procedure is illustrated using several examples taken from regression and classification, as well as density estimation applications.

Pre-CME onset fuses: do the STEREO heliospheric imagers hold the clues to the CME onset process?

Understanding the onset of coronal mass ejections (CMEs) is surely one of the holy grails of solar physics today. Inspection of data from the Heliospheric Imagers (HI), which are part of the SECCHI instrument suite aboard the two NASA STEREO spacecraft, appears to have revealed pre-eruption signatures which may provide valuable evidence for identifying the CME onset mechanism. Specifically, an examination of the HI images has revealed narrow rays comprised of a series of outward-propagating plasma blobs apparently forming near the edge of the streamer belt prior to many CME eruptions. In this pilot study, we inspect a limited dataset to explore the significance of this phenomenon, which we have termed a pre-CME ‘fuse’. Although, the enhanced expulsion of blobs may be consistent with an increase in the release of outward-propagating blobs from the streamers themselves, it could also be interpreted as evidence for interchange reconnection in the period leading to a CME onset. Indeed, it is argued that the latter could even have implications for the end-of-life of CMEs. Thus, the presence of these pre-CME fuses provides evidence that the CME onset mechanism is either related to streamer reconnection processes or the reconnection between closed field lines in the streamer belt and adjacent, open field lines. We investigate the nature of these fuses, including their timing and location with respect to CME launch sites, as well as their speed and topology.

Adding value to ecological risk assessment with population modeling

Current measures used to estimate the risks of toxic chemicals are not relevant to the goals of the environmental protection process, and thus ecological risk assessment (ERA) is not used as extensively as it should be as a basis for cost-effective management of environmental resources. Appropriate population models can provide a powerful basis for expressing ecological risks that better inform the environmental management process and thus that are more likely to be used by managers. Here we provide at least five reasons why population modeling should play an important role in bridging the gap between what we measure and what we want to protect. We then describe six actions needed for its implementation into management-relevant ERA.

Modeling data with structural and temporal correlation using lower level and higher level multilevel models

Novel imaging techniques are playing an increasingly important role in drug development, providing insight into the mechanism of action of new chemical entities. The data sets obtained by these methods can be large with complex inter-relationships, but the most appropriate statistical analysis for handling this data is often uncertain - precisely because of the exploratory nature of the way the data are collected. We present an example from a clinical trial using magnetic resonance imaging to assess changes in atherosclerotic plaques following treatment with a tool compound with established clinical benefit. We compared two specific approaches to handle the correlations due to physical location and repeated measurements: two-level and four-level multilevel models. The two methods identified similar structural variables, but higher level multilevel models had the advantage of explaining a greater proportion of variation, and the modeling assumptions appeared to be better satisfied.

Understanding the early stages of the innovation diffusion process: awareness, influence and communication networks

The themes of awareness and influence within the innovation diffusion process are addressed. The innovation diffusion process is typically represented as stages, yet awareness and influence are somewhat under-represented in the literature. Awareness and influence are situated within the contextual setting of individual actors but also within the broader institutional forces. Understanding how actors become aware of an innovation and then how their opinion is influenced is important for creating a more innovation-active UK construction sector. Social network analysis is proposed as one technique for mapping how awareness and influence occur and what they look like as a network. Empirical data are gathered using two modes of enquiry. This is done through a pilot study consisting of chartered professionals and then through a case study organization as it attempted to diffuse an innovation. The analysis demonstrates significant variations across actors’ awareness and influence networks. It is argued that social network analysis can complement other research methods in order to present a richer picture of how actors become aware of innovations and where they draw their influences regarding adopting innovations. In summarizing the findings, a framework for understanding awareness and influence associated with innovation within the UK construction sector is presented. Finally, with the UK construction sector continually being encouraged to be innovative, understanding and managing an actor’s awareness and influence network will be beneficial. The overarching conclusion thus describes the need not only to build research capacity in this area but also to push the boundaries related to the research methods employed.

The location of executive suites and business centers in the United States: an exploratory analysis

Increasingly, corporate occupiers seek more flexible ways of meeting their accommodation needs. One consequence of this process has been the growth of the executive suite, serviced office or business centre market. This paper, the final report of a research project funded by the Real Estate Research Institute, focuses upon the geographical distribution of business centers offering executive suites within the US. After a brief review of the development of the market, the paper examines the availability of data, provides basic descriptive statistics of the distribution of executive suites by state and by metropolitan statistical area and then attempts to model the distribution using demographic and socio-economic data at MSA level. The distribution reflects employment in key growth sectors and the position of the MSA in the urban hierarchy. An appendix presents a preliminary view of the global distribution of suites.

Location and collocation advantages in international innovation

Purpose – This paper examines the role of location-specific (L) advantages in the spatial distribution of multinational enterprise (MNE) R&D activity. The meaning of L advantages is revisited. In addition to L advantages that are industry-specific, the paper emphasises that there is an important category of L advantages, referred to as collocation advantages. Design/methodology/approach – Using the OLI framework, this paper highlights that the innovation activities of MNEs are about interaction of these variables, and the essential process of internalising L advantages to enhance and create firm-specific advantages. Findings – Collocation advantages derive from spatial proximity to specific unaffiliated firms, which may be suppliers, competitors, or customers. It is also argued that L advantages are not always public goods, because they may not be available to all firms at a similar or marginal cost. These costs are associated with access and internalisation of L advantages, and – especially in the case of R&D – are attendant with the complexities of embeddedness. Originality/value – The centralisation/decentralisation, spatial separation/collocation debates in R&D location have been mistakenly viewed as a paradox facing firms, instead of as a trade-off that firms must make.

Skilloscopy: Bayesian modeling of decision makers' skill

This paper proposes and demonstrates an approach, Skilloscopy, to the assessment of decision makers. In an increasingly sophisticated, connected and information-rich world, decision making is becoming both more important and more difficult. At the same time, modelling decision-making on computers is becoming more feasible and of interest, partly because the information-input to those decisions is increasingly on record. The aims of Skilloscopy are to rate and rank decision makers in a domain relative to each other: the aims do not include an analysis of why a decision is wrong or suboptimal, nor the modelling of the underlying cognitive process of making the decisions. In the proposed method a decision-maker is characterised by a probability distribution of their competence in choosing among quantifiable alternatives. This probability distribution is derived by classic Bayesian inference from a combination of prior belief and the evidence of the decisions. Thus, decision-makers’ skills may be better compared, rated and ranked. The proposed method is applied and evaluated in the gamedomain of Chess. A large set of games by players across a broad range of the World Chess Federation (FIDE) Elo ratings has been used to infer the distribution of players’ rating directly from the moves they play rather than from game outcomes. Demonstration applications address questions frequently asked by the Chess community regarding the stability of the Elo rating scale, the comparison of players of different eras and/or leagues, and controversial incidents possibly involving fraud. The method of Skilloscopy may be applied in any decision domain where the value of the decision-options can be quantified.

Analysis and modeling of ants’ behavior from single to multi-body

In order to shed light on the collective behavior of social insects, we analyzed the behavior of ants from single to multi-body. In an experimental set-up, ants are placed in hemisphere without a nest and food. Trajectory of ants is recorded. From this bottom-up approach, we found that collective behavior of ants as follows: 1. Activity of single ant increases and decreases periodically. 2. Spontaneous meeting process is observed between two ants and meeting spot of two ants is localized in hemisphere. 3. Result on division of labor is obtained between two ants.

Ontology modeling for generation of clinical pathways

Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP) as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM) is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM) is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP. Findings: This research confirms the necessity of taking into consideration social aspects in designing information systems and automating CP. The complexity of healthcare processes can be best tackled by analyzing stakeholders, which we treat as social agents, their goals and patterns of action within the agent network. Originality/value: The current modeling methods describe CPs from a structural aspect comprising activities, properties and interrelationships. However, these methods lack a mechanism to describe possible patterns of human behavior and the conditions under which the behavior will occur. To overcome this weakness, a semiotic approach to generation of clinical pathway is introduced. The CP generated from SAM together with norms will enrich the knowledge representation of the domain through ontology modeling, which allows the recognition of human responsibilities and obligations and more importantly, the ultimate power of decision making in exceptional circumstances.

Simultaneous lidar and EOS MLS measurements, and modeling, of a rare polar ozone filament event over Mauna Loa Observatory, Hawaii

In mid-March 2005, a rare lower stratospheric polar vortex filamentation event was observed simultaneously by the JPL lidar at Mauna Loa Observatory, Hawaii, and by the EOS MLS instrument onboard the Aura satellite. The event coincided with the beginning of the spring 2005 final warming. On 16 March, the filament was observed by lidar around 0600 UT between 415 K and 455 K, and by MLS six hours earlier. It was seen on both the lidar and MLS profiles as a layer of enhanced ozone, peaking at 1.7 ppmv in a region where the climatological values are usually around or below 1 ppmv. Ozone profiles measured by lidar and MLS were compared to profiles from the Chemical Transport Model MIMOSA-CHIM. The agreement between lidar, MLS, and the model is excellent considering the difference in the sampling techniques. MLS was also able to identify the filament at another location north of Hawaii.

Rhetoric in international standard setting process: constructing accounting reality

The paper seeks to explore in depth the ways in which rhetorical strategies are employed in the international accounting standard setting process. The study proposes that rather than simply detailing new accounting requirements, the texts and drafts of accounting standards are artefacts, i.e. deliberately and carefully crafted products, that construct, persuade and encourage certain beliefs and behaviours. The persuasive and constructive strategies are also employed by the constituents submitting comment letters on the regulatory proposals. Consequently, the international accounting standard setting process is an ‘interactive process of meaning making’ (Fairclough, 1989). The study regards accounting as a social construct based on intersubjectivity (Searle, 1995; Davidson, 1990, 1994) and posits language as a constitutive factor in the process (Saussure, 1916; Peirce, 1931-58). This approach to the use of language and the role of rhetoric as a persuasive tool to convince others to our perception of ‘accounting reality’ is supported by the sociological work of Bourdieu (1990, 1991). Bourdieu has drawn our attention to how language becomes used, controlled, reformed and reconstituted by the social agents for the purposes of establishing their dominance. In our study we explore in particular the joint IASB and FASB proposals and subsequent regulations on the scope of consolidation and relevant disclosures that address issues of off-balance sheet financing, a subject that is very timely and of great topical importance. The analysis has revealed sophisticated rhetorical devices used by both the Boards and by the lobbyists. These reflect Aristotelian ethos, pathos and logos. The research demonstrates that those using accounting standards as well as those reading comment letters on the proposals for new standards should be aware of the normative nature of these documents and the subjectivity inherent in the nature of the text.

A modified PNN algorithm with optimal PD modeling using the orthogonal least squares method

In this paper a modified algorithm is suggested for developing polynomial neural network (PNN) models. Optimal partial description (PD) modeling is introduced at each layer of the PNN expansion, a task accomplished using the orthogonal least squares (OLS) method. Based on the initial PD models determined by the polynomial order and the number of PD inputs, OLS selects the most significant regressor terms reducing the output error variance. The method produces PNN models exhibiting a high level of accuracy and superior generalization capabilities. Additionally, parsimonious models are obtained comprising a considerably smaller number of parameters compared to the ones generated by means of the conventional PNN algorithm. Three benchmark examples are elaborated, including modeling of the gas furnace process as well as the iris and wine classification problems. Extensive simulation results and comparison with other methods in the literature, demonstrate the effectiveness of the suggested modeling approach.

Location, control and innovation in knowledge-intensive industries

The rising share of intangibles in economies worldwide highlights the crucial role of knowledge-intensive and creative industries in current and future wealth generation. The recognition of this trend has led to intense competition in these industries. At the micro-level, firms from both advanced and emerging economies are globally dispersing their value chains to control costs and leverage capabilities. The geography of innovation is the outcome of a dynamic process whereby firms from emerging economies strive to catch-up with advanced economy competitors, creating strong pressures for continued innovation. However, two distinct strategies can be discerned with regard to the control of the value chain. A vertical integration strategy emphasizes taking advantage of ‘linkage economies’ whereby controlling multiple value chain activities enhances the efficiency and effectiveness of each one of them. In contrast, a specialization strategy focuses on identifying and controlling the creative heart of the value chain, while outsourcing all other activities. The global mobile handset industry is used as the template to illustrate the theory.