A switching model of dynamic asset selling problem

This paper proposes an asset selling problem with a new selling strategy called the switching strategy where multiple homogeneous assets on hand must be sold up to a specified deadline. At each point in time the seller is permitted to decide between 1) proposing a selling price up front to an appearing buyer and 2) concealing the price and letting the buyer come up with an offer. Our analysis indicates that under certain conditions there emerges a time threshold after which the seller switches from concealing his idea for the selling price to proposing this price, and vice versa.

Knowledge on road information in sub-urban lane detection via multiple cue integration

Detection of lane boundaries of a road based on the images or video taken by a video capturing device in a suburban environment is a challenging task. In this paper, a novel lane detection algorithm is proposed without considering camera parameters; which robustly detects lane boundaries in real-time especially for sub-urban roads. Initially, the proposed method fits the CIE L*a*b* transformed road chromaticity values (that is a* and b* values) to a bi-variate Gaussian model followed by the classification of road area based on Mahalanobis distance. Secondly, the classified road area acts as an arbitrary shaped region of interest (AROI) in order to extract blobs resulting from the filtered image by a two dimensional Gabor filter. This is considered as the first cue of images. Thirdly, another cue of images was employed in order to obtain an entropy image. Moreover, results from the color based image cue and entropy image cue were integrated following an outlier removing process. Finally, the correct road lane points are fitted with Bezier splines which act as control points that can form arbitrary shapes. The algorithm was implemented and experiments were carried out on sub-urban roads. The results show the effectiveness of the algorithm in producing more accurate lane boundaries on curvatures and other objects on the road.

The Civic School : Australian-Indonesian professional collaboration to model and audit the development of democratic primary classrooms and teacher language using the index for inclusion

The study is a pilot project in Australian-Indonesian institutional collaboration for the professional development of primary school teachers in West Sumatra in citizenship education. Senior staff in the department of Pancasila and Citizenship Education at the State University of Padang (UNP), West Sumatra initiated the project. UNP staff sought the collaboration of the Faculty of Education at the University of Tasmania for bringing about and sustaining changes in teacher practice needed to implement the new civic goals in the 1999 Suplemen. The Index for Inclusion was used to model and audit the development of democratic primary classrooms and language use in a cluster of Padang schools in West Sumatra. The paper describes the background to the project and how the Index for Inclusion was understood during the initial two-week implementation phase by teachers and school principals. The significance of the study lies in the potential of the Index for Inclusion internationally to citizenship education, a field of education that was not considered in the initial development of the Index project and the contribution of the multiple fields of inquiry to the evolving theoretical understandings of inclusive education.

Beliefs, values, and action : the judgment model of cognitive distortions in sexual offenders

In this paper, we present the Judgment Model of Cognitive Distortions (JMCD), a new model of cognitive distortions that spans multiple levels of analysis and contains different types of judgments. This model proposes that cognitive distortions tend to cluster together in what we have termed Thematic Networks (TN): judgments about beliefs, values, and actions. We argue that the three sets of judgments cover all types of cognitive distortions apparent in sexual offenders including those revolving around content (i.e., asserting characteristics to people, the offender, the world) and cognitive operations (i.e., denial, minimization, rationalizations). Following a description of the JMCD, we demonstrate how it can account for the cognitive schemata identified in sexual offenders by researchers and clinicians. The paper concludes with a brief discussion of the clinical and research implications of the JMCD.

A heuristic model selection scheme for representing hot flow data using the hot torsion test results

The problem of "model selection" for expressing a wide range of constitutive behaviour adequately using hot torsion test data was considered here using a heuristic approach. A model library including several nested parametric linear and non-linear models was considered and applied to a set of hot torsion test data for API-X 70 micro-alloyed steel with a range of strain rates and temperatures. A cost function comprising the modelled hot strength data and that of the measured data were utilized in a heuristic model selection scheme to identify the optimum models. It was shown that a non-linear rational model including ten parameters is an optimum model that can accurately express the multiple regimes of hardening and softening for the entire range of the experiment. The parameters for the optimum model were estimated and used for determining variations of hot strength of the samples with deformation.

Conceptualizing social influence in the ubiquitous computing era : technology adoption and use in multiple use contexts

Ubiquitous and mobile computing has increased the level of social connectedness. In an era where technology has permeated into spaces of work, play and socializing, social influence has become an important consideration. The operationalization of the social influence construct in the technology adoption and use literature often assumes singular technology use contexts and purposes. We question whether social influence, as operationalized in IS, is reflective of the utilitarian, hedonic and social environment that many individuals operate in. We propose a framework to consider social influence more inclusively, drawing on differences in referent power and levels of expertise. We outline our research approach within the demographic segment of young working professionals. Research in this area is necessary to improve theoretical explanations of adoptive behavior of these technologies. We hope to contribute by suggesting a richer, more encompassing operationalization of the social influence construct for future IS research.

A maturity model of enterprise business intelligence

The implementation of an enterprise-level business intelligence initiative is a large-scale and complex undertaking, involving significant expenditure and multiple stakeholders over a lengthy period. It is therefore imperative to have systematic guidelines for business intelligence stakeholders in referring business intelligence maturity levels. Draw upon the prudent concepts of the Capability Maturity Model, this research proposes a multi-dimensional maturity model with distinct maturity levels for managing enterprise business intelligence initiatives. The maturity model, named Enterprise Business Intelligence Maturiy (EBIM), consists of five core maturity levels and four key dimensions, namely information quality, master data management, warehousing architecture, and analytics. It can be used to assist enterprises in benchmarking their business intelligence maturity level and identifying the critical areas to attain higher level of maturity.

Multiple mating and a low incidence of cuckoldry for nest-holding males in the two-spotted goby, Gobiusculus flavescens

Background: A major question in behavioural ecology concerns the relationship between genetic mating systems and the strength of sexual selection. In this study, we investigated the genetic mating system of the two-spotted goby (Gobiusculus flavescens), a useful fish model for the study of sexual selection whose genetic mating system remains uncharacterized. We developed four polymorphic microsatellite markers and used them to conduct parentage analyses on 21 nests collected during the breeding season to examine the rates of multiple mating by males and to test for evidence of alternative mating strategies.

Results: Results of this study indicate that male G. flavescens mate with multiple females and enjoy confidence of paternity. We detected only one instance of sneaking, so cuckoldry contributed a very small percentage (~0.1%) of the total fertilizations in this population. Nests were nearly full and males that maintain larger nests have higher mating and reproductive success, irrespective of body size.

Conclusion: Overall, our investigation shows that G. flavescens is similar to other, related gobies in that the nests of care-giving males often contain eggs from multiple females. However, G. flavescens differs from other gobies in displaying an extremely low rate of cuckoldry. The study of ecological factors responsible for this important

Multiple vesicular morphologies in AB/AC diblock copolymer complexes through hydrogen bonding interactions

We report for the first time multiple vesicular morphologies in block copolymer complexes formed in aqueous media via hydrogen bonding interactions. A model AB/AC diblock copolymer system consisting of polystyrene-block- poly(acrylic acid) (PS-b-PAA) and polystyrene-block-poly(ethylene oxide) (PS-b-PEO) was examined using transmission electron microscopy, small-angle X-ray scattering, and dynamic light scattering. The complexation and morphological transitions were driven by the hydrogen bonding between the complementary binding sites on PAA and PEO blocks of the two diblock copolymers. Upon the addition of PS-b-PEO, a variety of bilayer aggregates were formed in PS-b-PAA/PS-b-PEO complexes including vesicles, multilamellar vesicles (MLVs), thick-walled vesicles (TWVs), interconnected compound vesicles (ICCVs), and irregular aggregates. Among these aggregates, ICCVs were observed as a new morphology. The morphology of aggregates was correlated with respect to the molar ratio of PEO to PAA. At [EO]/[AA] = 0.5, vesicles were observed, while MLVs were obtained at [EO]/[AA] = 1. TWVs and ICCVs were formed at [EO]/[AA] = 2 and 6, respectively. When [EO]/[AA] reached 8 and above, only irregular aggregates appeared. These findings suggest that complexation between two amphiphilic diblock copolymers is a viable approach to prepare polymer vesicles in aqueous media.

Spectral element model updating for damage identification using clonal selection algorithm

A spectral element model updating procedure is presented to identify damage in a structure using Guided wave propagation results. Two damage spectral elements (DSE1 and DSE2) are developed to model the local (cracks in reinforcement bar) and global (debonding between reinforcement bar and concrete) damage in one-dimensional homogeneous and composite waveguide, respectively. Transfer matrix method is adopted to assemble the stiffness matrix of multiple spectral elements. In order to solve the inverse problem, clonal selection algorithm is used for the optimization calculations. Two displacement-based functions and two frequency-based functions are used as objective functions in this study. Numerical simulations of wave propagation in a bare steel bar and in a reinforcement bar without and with various assumed damage scenarios are carried out. Numerically simulated data are then used to identify local and global damage of the steel rebar and the concrete-steel interface using the proposed method. Results show that local damage is easy to be identified by using any considered objective function with the proposed method while only using the wavelet energy-based objective function gives reliable identification of global damage. The method is then extended to identify multiple damages in a structure. To further verify the proposed method, experiments of wave propagation in a rectangular steel bar before and after damage are conducted. The proposed method is used to update the structural model for damage identification. The results demonstrate the capability of the proposed method in identifying cracks in steel bars based on measured wave propagation data.

An adjustable force field for multiple robot mission and path planning

Mission and path planning for multiple robots in dynamic environments is required when multiple mobile robots or unmanned vehicles are used for geographically distributed tasks. Assigning tasks and paths for robots for cooperatively accomplishing a mission of reaching to number of target points are addressed in this paper. The methodology that is proposed is based on using an adjustable force field which is suitable for dynamic environment. From the force field analysis, the decisions to assign tasks for each robot are then made. The force field is also used to plan a collision free path for each robot. Adjustable weights for the force field model are proposed to satisfy the constraints of the motion. In this research, the constraints are the cooperation of the robots, the precedence between the targets and between robots, and the discrimination between different obstacles. Two simulations for mission and path planning in 2D and 3D dynamic spaces with multiple robots are presented based on the proposed adjustable force filed. The result of the mission and path planning for three robots cooperatively doing eight target points are shown.

Multiple actuator fault tolerance for static nonlinear systems based on minimum velocity jump

Static nonlinear systems are common when the model of the kinematics of mechanical or civil structures is analyzed for instance kinematics of robotic manipulators. This paper addresses the maximum effort toward fault tolerance for any number of the locked actuators failures in static nonlinear systems. It optimally reconfigures the inputs via a mapping that maximally accommodates the failures. The mapping maps the failures to an extra action of healthy actuators that results to a minimum jump for the velocity of the output variables. Then from this mapping, the minimum jump of the velocity of the output is calculated. The conditions for a zero velocity jump of the output variables are discussed. This shows that, when the conditions of fault tolerance are maintained, the proposed framework is capable of fault recovery not only at fault instances but also at the whole output trajectory. The proposed mapping is validated by three case studies.

A social network analysis model for analysing stakeholder-associated safety risks in infrastructure projects

An important strategy in the long-term blueprint for making Australia's 18 capital and major regional cities more productive, sustainable and liveable is to develop high quality public infrastructure systems to improve civic quality of life. Because of the unique features of construction activities, such as long period, complicated processes, and dynamic organizational structures, infrastructure projects normally involve multiple stakeholders and are subject to various risks, especially safety issues. Any negligence or mismanagement of critical safety risks will have huge impact on achieving project objectives and success. Although many previous studies have identified and assessed various safety risks in construction industry, a main research gap is that these studies ignored a fact that most risks are interrelated and associated with internal and external stakeholders of the projects. The lack of a theoretical foundation and appropriate methods for analysing stakeholder-associated safety risks and their interdependencies in infrastructure projects hinders effective risk management processes and the formulations of decision strategies. This research aims at enabling higher performance in strategic safety risk management in infrastructure projects through the development of a holistic risk analysis model using Stakeholder and Social Network Theories. The outcomes can broaden project managers' awareness of emerging influential safety risks and enhance their ability to perceive, understand, assess, and mitigate safety risks in an effective and efficient way; thereby higher performance in strategic risk management could be achieved in infrastructure projects.

Identifying multi-view patterns with hierarchy and granularity based multimodal (HGM) cognitive model

Humans perceive entities such as objects, patterns, events, etc. as concepts, which are the basic units in human intelligence and communications. In addition, perceptions of these entities could be abstracted and generalised at multiple levels of granularity. In particular, such granulation allows the formation and usage of concepts in human intelligence. Such natural granularity in human intelligence could inspire and motivate the design and development of pattern identification approach in Data Mining. In our opinion, a pattern could be perceived at multiple levels of granularity and thus we advocate for the co-existence of hierarchy and granularity. In addition, granular patterns exist across different sources of data (multimodality). In this paper, we present a cognitive model that incorporates the characteristics of Hierarchy, Granularity and Multimodality for multi-view patterns identification in crime domain. Such framework is implemented with Growing Self Organising Maps (GSOM) and some experimental results are presented and discussed.