An integrated multi-stage model of knowledge management in international joint ventures: identifying a trigger for knowledge exploration and knowledge harvest

This paper examines the evolution of knowledge management from the initial knowledge migration stage, through adaptation and creation, to the reverse knowledge migration stage in international joint ventures (IJVs). While many studies have analyzed these stages (mostly focusing on knowledge transfer), we investigated the path-dependent nature of knowledge flow in IJVs. The results from the empirical analysis based on a survey of 136 Korean parent companies of IJVs reveal that knowledge management in IJVs follows a sequential, multi-stage process, and that the knowledge transferred from parents to IJVs must first be adapted within its new environment before it reaches the creation stage. We also found that only created knowledge is transferred back to parents.

Dual semiosis analysis model managing customer-focused service innovation

Customers will not continue to pay for a service if it is perceived to be of poor quality, and/or of no value. With a paradigm shift towards business dependence on service orientated IS solutions [1], it is critical that alignment exists between service definition, delivery, and customer expectation, businesses are to ensure customer satisfaction. Services, and micro-service development, offer businesses a flexible structure for solution innovation, however, constant changes in technology, business and societal expectations means an iterative analysis solution is required to i) determine whether provider services adequately meet customer segment needs and expectations, and ii) to help guide business service innovation and development. In this paper, by incorporating multiple models, we propose a series of steps to help identify and prioritise service gaps. Moreover, the authors propose the Dual Semiosis Analysis Model, i.e. a tool that highlights where within the symbiotic customer / provider semiosis process, requirements misinterpretation, and/or service provision deficiencies occur. This paper offers the reader a powerful customer-centric tool, designed to help business managers highlight both what services are critical to customer quality perception, and where future innovation

Analysis Scheme in the Ensemble Kalman Filter

This paper discusses an important issue related to the implementation and interpretation of the analysis scheme in the ensemble Kalman filter . I t i s shown that the obser vations must be treated as random variables at the analysis steps. That is, one should add random perturbations with the correct statistics to the obser vations and generate an ensemble of obser vations that then is used in updating the ensemble of model states. T raditionally , this has not been done in previous applications of the ensemble Kalman filter and, as will be shown, this has resulted in an updated ensemble with a variance that is too low . This simple modification of the analysis scheme results in a completely consistent approach if the covariance of the ensemble of model states is interpreted as the prediction error covariance, and there are no further requirements on the ensemble Kalman filter method, except for the use of an ensemble of sufficient size. Thus, there is a unique correspondence between the error statistics from the ensemble Kalman filter and the standard Kalman filter approach

Sparse density estimation on multinomial manifold combining local component analysis

A new sparse kernel density estimator is introduced based on the minimum integrated square error criterion combining local component analysis for the finite mixture model. We start with a Parzen window estimator which has the Gaussian kernels with a common covariance matrix, the local component analysis is initially applied to find the covariance matrix using expectation maximization algorithm. Since the constraint on the mixing coefficients of a finite mixture model is on the multinomial manifold, we then use the well-known Riemannian trust-region algorithm to find the set of sparse mixing coefficients. The first and second order Riemannian geometry of the multinomial manifold are utilized in the Riemannian trust-region algorithm. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with competitive accuracy to existing kernel density estimators.

Time-frequency analysis of acoustic noise produced by breaking of crisp biscuits

This paper demonstrates by means of joint time-frequency analysis that the acoustic noise produced by the breaking of biscuits is dependent on relative humidity and water activity. It also shows that the time-frequency coefficients calculated using the adaptive Gabor transformation algorithm is dependent on the period of time a biscuit is exposed to humidity. This is a new methodology that can be used to assess the crispness of crisp foods. (c) 2007 Elsevier Ltd. All rights reserved.

Thermodynamic and statistical analysis of soybean oil extraction process using renewable solvent

The main goal of this work was to evaluate thermodynamic parameters of the soybean oil extraction process using ethanol as solvent. The experimental treatments were as follows: aqueous solvents with water contents varying from 0 to 13% (mass basis) and extraction temperature varying from 50 to 100 degrees C. The distribution coefficients of oil at equilibrium have been used to calculate enthalpy, entropy and free energy changes. The results indicate that oil extraction process with ethanol is feasible and spontaneous, mainly under higher temperature. Also, the influence of water level in the solvent and temperature were analysed using the response surface methodology (RSM). It can be noted that the extraction yield was highly affected by both independent variables. A joint analysis of thermodynamic and RSM indicates the optimal level of solvent hydration and temperature to perform the extraction process.

Bothrops insularis venomics: A proteomic analysis supported by transcriptomic-generated sequence data

A joint transcriptomic and proteomic approach employing two-dimensional electrophoresis, liquid chromatography and mass spectrometry was carried out to identify peptides and proteins expressed by the venom gland of the snake Bothrops insularis, an endemic species of Queimada Grande Island, Brazil. Four protein families were mainly represented in processed spots, namely metalloproteinase, serine proteinase, phospholipase A(2) and lectin. Other represented families were growth factors, the developmental protein G10, a disintegrin and putative novel bradykinin-potentiating peptides. The enzymes were present in several isoforms. Most of the experimental data agreed with predicted values for isoelectric point and M(r) of proteins found in the transcriptome of the venom gland. The results also support the existence of posttranslational modifications and of proteolytic processing of precursor molecules which could lead to diverse multifunctional proteins. This study provides a preliminary reference map for proteins and peptides present in Bothrops insularis whole venom establishing the basis for comparative studies of other venom proteomes which could help the search for new drugs and the improvement of venom therapeutics. Altogether, our data point to the influence of transcriptional and post-translational events on the final venom composition and stress the need for a multivariate approach to snake venomics studies. (c) 2009 Elsevier B.V. All rights reserved.

Morphometric analysis of the AMPA-type neurons in the Deiters vestibular complex of the chick brain

Chicken (Gallus gallus) brains were used to investigate the typology and the immunolabel pattern for the subunits composing the AMPA-type glutamate receptors (GluR) of hindbrain neurons of the dorsal (dND) and ventral nuclei (vND) of the Deiter`s vestibular complex (CD), which is the avian correspondent of the lateral vestibular nucleus (LVN) of mammals. Our results revealed that neurons of both divisions were poor in GluR1. The vND, the GluR2/3+ and GluR4+ label presented no area or neuronal size preference, although most neurons were around 75%. The dND neurons expressing GluR2/3 are primarily around 85%, medium to large-sized 85%, and predominantly 60% located in the medial portion of the rostral pole and in the lateral portion of the caudal pole. The majority of dND neurons containing GluR4 are also around 75%, larger (70% are large and giant), exhibiting a distribution that seems to be complementary to that of GluR2/3+ neurons. This distinct arrangement indicates functional differences into and between the DC nuclei, also signaling that such variation could be attributed to the diverse nature of the subunit composition of the GluRs. Discussion addresses the morphological and functional correlation of the avian DC with the LVN of mammals in addition to the high morphological correspondence, To include these data into the modern comparative approach we propose to adopt a similar nomenclature for the avian divisions dND and vND that could be referred as dLVN and vLVN. (C) 2008 Elsevier B.V. All rights reserved.

PAR(2) and Temporomandibular Joint Inflammation in the Rat

The proteinase-activated receptor 2 (PAR(2)) is a putative therapeutic target for arthritis. We hypothesized that the early pro-inflammatory effects secondary to its activation in the temporomandibular joint (TMJ) are mediated by neurogenic mechanisms. Immunofluorescence analysis revealed a high degree of neurons expressing PAR(2) in retrogradely labeled trigeminal ganglion neurons. Furthermore, PAR(2) immunoreactivity was observed in the lining layer of the TMJ, co-localizing with the neuronal marker PGP9.5 and substance-P-containing peripheral sensory nerve fibers. The intra-articular injection of PAR(2) agonists into the TMJ triggered a dose-dependent increase in plasma extravasation, neutrophil influx, and induction of mechanical allodynia. The pharmacological blockade of natural killer 1 (NK(1)) receptors abolished PAR(2)-induced plasma extravasation and inhibited neutrophil influx and mechanical allodynia. We conclude that PAR(2) activation is proinflammatory in the TMJ, through a neurogenic mechanism involving NK(1) receptors. This suggests that PAR(2) is an important component of innate neuro-immune response in the rat TMJ.

On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.

Upgrading a TCABR data analysis and acquisition system for remote participation using Java, XML, RCP and modern client/server communication/authentication

The TCABR data analysis and acquisition system has been upgraded to support a joint research programme using remote participation technologies. The architecture of the new system uses Java language as programming environment. Since application parameters and hardware in a joint experiment are complex with a large variability of components, requirements and specification solutions need to be flexible and modular, independent from operating system and computer architecture. To describe and organize the information on all the components and the connections among them, systems are developed using the extensible Markup Language (XML) technology. The communication between clients and servers uses remote procedure call (RPC) based on the XML (RPC-XML technology). The integration among Java language, XML and RPC-XML technologies allows to develop easily a standard data and communication access layer between users and laboratories using common software libraries and Web application. The libraries allow data retrieval using the same methods for all user laboratories in the joint collaboration, and the Web application allows a simple graphical user interface (GUI) access. The TCABR tokamak team in collaboration with the IPFN (Instituto de Plasmas e Fusao Nuclear, Instituto Superior Tecnico, Universidade Tecnica de Lisboa) is implementing this remote participation technologies. The first version was tested at the Joint Experiment on TCABR (TCABRJE), a Host Laboratory Experiment, organized in cooperation with the IAEA (International Atomic Energy Agency) in the framework of the IAEA Coordinated Research Project (CRP) on ""Joint Research Using Small Tokamaks"". (C) 2010 Elsevier B.V. All rights reserved.

Texture analysis and classification using deterministic tourist walk

In this paper, we present a study on a deterministic partially self-avoiding walk (tourist walk), which provides a novel method for texture feature extraction. The method is able to explore an image on all scales simultaneously. Experiments were conducted using different dynamics concerning the tourist walk. A new strategy, based on histograms. to extract information from its joint probability distribution is presented. The promising results are discussed and compared to the best-known methods for texture description reported in the literature. (C) 2009 Elsevier Ltd. All rights reserved.

A complex network-based approach for boundary shape analysis

This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has all efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on three image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, Curvature, Zernike moments and multiscale fractal dimension). (C) 2008 Elsevier Ltd. All rights reserved.

STABILITY ANALYSIS WITH APPLICATIONS OF A TWO-DIMENSIONAL DYNAMICAL SYSTEM ARISING FROM A STOCHASTIC MODEL FOR AN ASSET MARKET

We analyze the stability properties of equilibrium solutions and periodicity of orbits in a two-dimensional dynamical system whose orbits mimic the evolution of the price of an asset and the excess demand for that asset. The construction of the system is grounded upon a heterogeneous interacting agent model for a single risky asset market. An advantage of this construction procedure is that the resulting dynamical system becomes a macroscopic market model which mirrors the market quantities and qualities that would typically be taken into account solely at the microscopic level of modeling. The system`s parameters correspond to: (a) the proportion of speculators in a market; (b) the traders` speculative trend; (c) the degree of heterogeneity of idiosyncratic evaluations of the market agents with respect to the asset`s fundamental value; and (d) the strength of the feedback of the population excess demand on the asset price update increment. This correspondence allows us to employ our results in order to infer plausible causes for the emergence of price and demand fluctuations in a real asset market. The employment of dynamical systems for studying evolution of stochastic models of socio-economic phenomena is quite usual in the area of heterogeneous interacting agent models. However, in the vast majority of the cases present in the literature, these dynamical systems are one-dimensional. Our work is among the few in the area that construct and study analytically a two-dimensional dynamical system and apply it for explanation of socio-economic phenomena.