Managing knowledge for asset management : shifting from process to relational frames

The purpose of this paper is to review existing knowledge management (KM) practices within the field of asset management, identify gaps, and propose a new approach to managing knowledge for asset management. Existing approaches to KM in the field of asset management are incomplete with the focus primarily on the application of data and information systems, for example the use of an asset register. It is contended these approaches provide access to explicit knowledge and overlook the importance of tacit knowledge acquisition, sharing and application. In doing so, current KM approaches within asset management tend to neglect the significance of relational factors; whereas studies in the knowledge management field have showed that relational modes such as social capital is imperative for ef-fective KM outcomes. In this paper, we argue that incorporating a relational ap-proach to KM is more likely to contribute to the exchange of ideas and the devel-opment of creative responses necessary to improve decision-making in asset management. This conceptual paper uses extant literature to explain knowledge management antecedents and explore its outcomes in the context of asset man-agement. KM is a component in the new Integrated Strategic Asset Management (ISAM) framework developed in conjunction with asset management industry as-sociations (AAMCoG, 2012) that improves asset management performance. In this paper we use Nahapiet and Ghoshal’s (1998) model to explain antecedents of relational approach to knowledge management. Further, we develop an argument that relational knowledge management is likely to contribute to the improvement of the ISAM framework components, such as Organisational Strategic Manage-ment, Service Planning and Delivery. The main contribution of the paper is a novel and robust approach to managing knowledge that leads to the improvement of asset management outcomes.

Very high resolution optical satellites for DEM generation : a review

The advent of very high resolution (VHR) optical satellites capable of producing stereo images led to a new era in extracting digital elevation model which commenced with the launch of IKONOS. The special specifications of VHR optical satellites besides, the significant economic profit stimulated other countries and companies to have their constellations such as EROS-A1 and EROS-B1 as the cooperation between Israel and ImageSat. QuickBird, WorldView-1 and WorldVew-2 were launched by DigitalGlobe. ALOS and GeoEye-1 were offered by Japan and GeoEye Respectively. In addition to aforementioned satellites, Indian and South Korea initiated their own constellation by launching CartoSat-1 and KOPOSAT-2 respectively.The availability of all so-called satellites make a huge market of stereo images for extracting of digital elevation model and other correspondent applications such as, producing orthorectifcatin images and updating maps. Therefore, there is a need for a comprehensive comparison for scientific and commercial clients to choose appropriate satellite images and methods of generating digital elevation model to obtain optimum results. This paper will thus give a review about the specifications of VHR optical satellites. Then it will discuss the automatic elaborating of digital elevation model. Finally an overview of studies and corresponding results is reported.

Conservation communication camp : come with ideas, leave with a plan

IUCN´s core work involves generating knowledge and tools to influence policy and practice for nature conservation. Whilst it appears that we are collectively making progress in some areas, we acknowledge the need to improve our communication processes and practices to ´move to action´ in this regard. We need to extend the influence of the science and the knowledge beyond the documents to achieve effective impact and action. The training course will focus on the process of getting the conservation messages out to a wider audience. This interactive and participatory training course will develop the skills and knowledge needed to communicate effective conservation messages for a range of IUCN internal and external audiences. The course will cover: • what is communication for conservation? • the communication planning process (developing your communication objectives) • identifying and understanding your target audiences • developing your conservation message • choosing your communication media and • evaluating the effectiveness of your communication strategies. A unique feature of the training course will be the use of Web 2.0 tools in innovative conservation communications e.g. use of social media in concept branding and social marketing. In the spirit of the Forum´s objective of ´Sharing know how´, each participant will bring a current conservation issue to the training course and will leave with their own communication plan. Potentially, the training course adopts a cross-thematic approach as the issues addressed could be drawn from any of the IUCN´s program themes. Primarily though, the training course´s best fit is with the ´Valuing and Conserving Biodiversity´ theme since it will provide concrete and pragmatic solutions to enhancing the implementation of conservation measures through participatory planning and capacity building.

A frontier functions approach to optimal scales of sustainable production

This paper translates the concepts of sustainable production to three dimensions of economic, environmental and ecological sustainability to analyze optimal production scales by solving optimizing problems. Economic optimization seeks input-output combinations to maximize profits. Environmental optimization searches for input-output combinations that minimize the polluting effects of materials balance on the surrounding environment. Ecological optimization looks for input-output combinations that minimize the cumulative destruction of the entire ecosystem. Using an aggregate space, the framework illustrates that these optimal scales are often not identical because markets fail to account for all negative externalities. Profit-maximizing firms normally operate at the scales which are larger than optimal scales from the viewpoints of environmental and ecological sustainability; hence policy interventions are favoured. The framework offers a useful tool for efficiency studies and policy implication analysis. The paper provides an empirical investigation using a data set of rice farms in South Korea.

An MRF based abnormal event detection approach using motion and appearance features

Abnormal event detection has attracted a lot of attention in the computer vision research community during recent years due to the increased focus on automated surveillance systems to improve security in public places. Due to the scarcity of training data and the definition of an abnormality being dependent on context, abnormal event detection is generally formulated as a data-driven approach where activities are modeled in an unsupervised fashion during the training phase. In this work, we use a Gaussian mixture model (GMM) to cluster the activities during the training phase, and propose a Gaussian mixture model based Markov random field (GMM-MRF) to estimate the likelihood scores of new videos in the testing phase. Further-more, we propose two new features: optical acceleration, and the histogram of optical flow gradients; to detect the presence of any abnormal objects and speed violations in the scene. We show that our proposed method outperforms other state of the art abnormal event detection algorithms on publicly available UCSD dataset.

Robust clustering of multi-type relational data via a heterogeneous manifold ensemble

High-Order Co-Clustering (HOCC) methods have attracted high attention in recent years because of their ability to cluster multiple types of objects simultaneously using all available information. During the clustering process, HOCC methods exploit object co-occurrence information, i.e., inter-type relationships amongst different types of objects as well as object affinity information, i.e., intra-type relationships amongst the same types of objects. However, it is difficult to learn accurate intra-type relationships in the presence of noise and outliers. Existing HOCC methods consider the p nearest neighbours based on Euclidean distance for the intra-type relationships, which leads to incomplete and inaccurate intra-type relationships. In this paper, we propose a novel HOCC method that incorporates multiple subspace learning with a heterogeneous manifold ensemble to learn complete and accurate intra-type relationships. Multiple subspace learning reconstructs the similarity between any pair of objects that belong to the same subspace. The heterogeneous manifold ensemble is created based on two-types of intra-type relationships learnt using p-nearest-neighbour graph and multiple subspaces learning. Moreover, in order to make sure the robustness of clustering process, we introduce a sparse error matrix into matrix decomposition and develop a novel iterative algorithm. Empirical experiments show that the proposed method achieves improved results over the state-of-art HOCC methods for FScore and NMI.

Transmittance properties of contact lens multipurpose solutions and their effects on a hydrogel lens

Purpose The aim was to assess the compatibility of different multipurpose solutions (MPSs) with one type of silicone hydrogel (SiH) contact lens by, assessing the changes in both ultraviolet (UV) and visible light transmissibility of the hydrogel lens caused by the MPSs. Methods The light transmittance from 200-700 nm were measured for the lotrafilcon B blister pack solution (BPS), six MPSs namely, ReNuMultiPlus Multi-Purpose Solution (Bausch and Lomb Inc., Rochester NY, USA.); Complete RevitaLens Multi-Purpose (Abbott Medical Optics Inc., Quarryvale Co. Dublin, Ireland); All In One Light (Sauflon Pharmaceuticals Ltd., Twickenham, England); SOLO-care AQUA™ (Ciba Vision Corporation Duluth, Georgia, USA.); Biomedics All-in-one solution (CooperVision, Hamble, UK); and HippiaMultiPlus All-in-one solution (Interojo Inc., Kyeonggi-do, Korea), and a lotrafilcon B SiH lens (before and after storage), using a spectrophotometer. Results The UV transmitted through the BPS and the MPS were similar (p >.05, for all), except for the HippiaMultiPlus which was lower (p < 0.001) by 19.8%. Mean transparency values were statistically (p<.001) significantly different between the BPS and the MPSs. All MP solution/SiH lens combinations resulted in relatively high UV transmittance values especially in the UVC spectrum, and significantly increased (p <.001) the visible light transmittance values of the SiH lens. Greater changes in transparency were observed in the ReNu/SiH lens (28.5%) and the Complete RevitaLens/SiH lens (24.9%) combinations. Conclusion The six MPSs showed significant variations in the transmitted UV and visible light. Similar to the BPS, all MPSs were equally transparent, but showed very poor UVA & UVB attenuation, except for the Hippia MultiPlus. The MPS/SiH lens combinations did not significantly affect the lens transparency but it significant increased the lens transmittance of UV radiation, after storage. Further in-vivo studies are needed to validate if this effect is constant.

All about that base : differing player experiences in video game genres and the unique case of MOBA games

Video games provide unique interactive player experiences (PX) often categorised into different genres. Prior research has looked at different game genres, but rarely through a PX lens. Especially, PX in the emerging area of massive online battle arena (MOBA) games is not well understood by researchers in the field. We address this knowledge gap by presenting a PX study of different game genres, which we followed up with a second semi-structured interview study about PX in MOBA games. Among the results of our analyses are that games that are likely played with other players, such as MOBA games, stimulate less immersion and presence for players. Additionally, while challenge and frustration are significantly higher in this genre, players get a sense of satisfaction from teamwork, competition and mastery of complex gameplay interactions. Our study is the first to contribute a comprehensive insight into key motivators of MOBA players and how PX in this genre is different from other genres.

Using conservation evidence to guide management

Almost 10 years ago, Pullin and Knight (2001) called for an “effectiveness revolution in conservation” to be enabled by the systematic evaluation of evidence for conservation decision making. Drawing from the model used in clinicalmedicine, they outlined the concept of “evidencebased conservation” in which existing information, or evidence, from relevant and rigorous research is compiled and analyzed in a systematic manner to inform conservation actions (Cochrane 1972). The promise of evidencebased conservation has generated significant interest; 25 systematic reviews have been completed since 2004 and dozens are underway (Collaboration for Environmental Evidence 2010). However we argue that an “effectiveness revolution” (Pullin & Knight 2001) in conservation will not be possible unless mechanisms are devised for incorporating the growing evidence base into decision frameworks. For conservation professionals to accomplish the missions of their organizations they must demonstrate that their actions actually achieve objectives (Pullin & Knight 2009). Systematic evaluation provides a framework for objectively evaluating the effectiveness of actions. To leverage the benefit of these evaluations, we need resource-allocation systems that are responsive to their outcomes. The allocation of conservation resources is often the product of institutional priorities or reliance on intuition (Sutherland et al. 2004; Pullin & Knight 2005; Cook et al. 2010). We highlight the NICE technologyappraisal process because it provides an example of formal integration of systematic-evidence evaluation with provision of guidance for action. The transparent process, which clearly delineates costs and benefits of each alternative action, could also provide the public with new insight into the environmental effects of different decisions. This insight could stimulate a wider discussion about investment in conservation by demonstrating how changes in funding might affect the probability of achieving conservation objectives. ©2010 Society for Conservation Biology

Automotive modal lock-in: The role of path dependence and large socio-economic regimes in market failure

This paper addresses less recognised factors which influence the diffusion of a particular technology. While an innovation’s attributes and performance are paramount, many fail because of external factors which favour an alternative. This paper, with theoretic input from diffusion, lock-in and path-dependency, presents a qualitative study of external factors that influenced the evolution of transportation in USA. This historical account reveals how one technology and its emergent systems become dominant while other choices are overridden by socio-political, economic and technological interests which include not just the manufacturing and service industries associated with the automobile but also government and market stakeholders. Termed here as a large socio-economic regime (LSER),its power in ensuring lock-in and continued path-dependency is shown to pass through three stages, weakening eventually as awareness improves. The study extends to transport trends in China, Korea, Indonesia and Malaysia and they all show the dominant role of an LSER. As transportation policy is increasingly accountable to address both demand and environmental concerns and innovators search for solutions, this paper presents important knowledge for innovators, marketers and policy makers for commercial and societal reasons, especially when negative externalities associated with an incumbent transportation technology may lead to market failure.

Process visualization techniques for multi-perspective process comparisons

Organizations executing similar business processes need to understand the differences and similarities in activities performed across work environments. Presently, research interest is directed towards the potential of visualization for the display of process models, to support users in their analysis tasks. Although recent literature in process mining and comparison provide several methods and algorithms to perform process and log comparison, few contributions explore novel visualization approaches. This paper analyses process comparison from a design perspective, providing some practical visualization techniques as anal- ysis solutions (/to support process analysis). The design of the visual comparison has been tackled through three different points of view: the general model, the projected model and the side-by-side comparison in order to support the needs of business analysts. A case study is presented showing the application of process mining and visualization techniques to patient treatment across two Australian hospitals.

Introducing telemetrics

This paper introduces a new methodology for analyzing and measuring engagement with television content by users of Twitter. Drawing on factors such as the network, viewing audience, and date of broadcast to establish a baseline expectation for volume of tweets around a television show, and applying techniques from the field of sabermetrics to create neutral volume figures (‘weighted tweets’) which exclude these variables, our metrics provide new insights into television’s social media presence. The methodology provides a variety of new measures for analysing the social media strategies of individual television programs, channels and networks, for comparing users’ engagement with programs, channels or networks, and for predicting future volumes of tweets.

Autonomous helicopter hover using an artificial neural network

Details the developments to date of an unmanned air vehicle (UAV) based on a standard size 60 model helicopter. The design goal is to have the helicopter achieve stable hover with the aid of an INS and stereo vision. The focus of the paper is on the development of an artificial neural network (ANN) that makes use of only the INS data to generate hover commands, which are used to directly manipulate the flight servos. Current results show that networks incorporating some form of recurrency (state history) offer little advantage over those without. At this stage, the ANN has partially maintained periods of hover even with misaligned sensors.