Applicability of a Neuroprobabilistic Integral Risk Index for the Environmental Management of Polluted Areas: A Case Study

Recently, we developed a GIS-Integrated Integral Risk Index (IRI) to assess human health risks in areas with presence of environmental pollutants. Contaminants were previously ranked by applying a self-organizing map (SOM) to their characteristics of persistence, bioaccumulation, and toxicity in order to obtain the Hazard Index (HI). In the present study, the original IRI was substantially improved by allowing the entrance of probabilistic data. A neuroprobabilistic HI was developed by combining SOM and Monte Carlo analysis. In general terms, the deterministic and probabilistic HIs followed a similar pattern: polychlorinated biphenyls (PCBs) and light polycyclic aromatic hydrocarbons (PAHs) were the pollutants showing the highest and lowest values of HI, respectively. However, the bioaccumulation value of heavy metals notably increased after considering a probability density function to explain the bioaccumulation factor. To check its applicability, a case study was investigated. The probabilistic integral risk was calculated in the chemical/petrochemical industrial area of Tarragona (Catalonia, Spain), where an environmental program has been carried out since 2002. The risk change between 2002 and 2005 was evaluated on the basis of probabilistic data of the levels of various pollutants in soils. The results indicated that the risk of the chemicals under study did not follow a homogeneous tendency. However, the current levels of pollution do not mean a relevant source of health risks for the local population. Moreover, the neuroprobabilistic HI seems to be an adequate tool to be taken into account in risk assessment processes.     

Efficient Algorithms for Determining 3-D Bi-Plane Imaging Geometry

Biplane projection imaging is one of the primary methods for imaging and visualizing the cardiovascular system in medicine. A key problem in such a technique is to determine the imaging geometry (i.e., the relative rotation and translation) of two projections so that the 3-D structure can be accurately reconstructed. Based on interesting observations and efficient geometric techniques, we present in this paper new algorithmic solutions for this problem. Comparing with existing optimization-based approaches, our techniques yield better accuracy and have bounded execution time, thus is more suitable for on-line applications. Our techniques can easily detect outliers to further improve the accuracy.This research was supported in part by NIH under USPHS grant numbers HL52567.     

Internationalization,Innovation and Institutions: The 3 I's Underpinning the Competitiveness of Emerging Market Firms

The past decade has seen an increase in the extent of research focused on and around emerging market firms (EMFs) and their rising levels of competitiveness in both their home markets and more importantly in the global market place. At the same time, the practitioner-oriented literature has been documenting a growing number of corporate success stories that originate in emerging market economies. We posit that the growing prominence of EMFs is a result of three interrelated phenomena: the fast-paced internationalization of EMFs into both developing and developed market economies; the rapidly increasing extent to which business enterprises in emerging economies are focusing on knowledge-intensive processes and innovation; and the continuous evolution of institutions in these markets, particularly in terms of economic liberalization.     

The soft side of knowledge transfer partnerships between universities and small to medium enterprises: an exploratory study to understand process improvement

Abstract

The study explores the soft side of knowledge transfer partnerships between universities and small to medium enterprises (SMEs), a topic which is often neglected in the knowledge management literature. The aim of this paper is to uncover the issues which emerge during formation of a partnership between heterogeneous organizations and universities. In addition, the study unfolds the criticalities of typical process improvement capability that supports the knowledge transfer partnerships between universities and SMEs. Using multiple cases, this study unravels the dominant elements that influence knowledge transfer process development, governance, implications and responsibilities. The major contribution of this study is the development of a framework based on empirical evidence using three knowledge transfer partnerships (KTPs) which illustrates the way in which soft factors in knowledge transfer partnership phases may have an impact on success or failure of university–industry collaborations for innovation.     

A Lean transportation approach for improving emergency medical operations

Abstract

This paper extends the approach of Lean transportation to improve the performance of emergency medical processes (EMP) by adapting its main concepts into the main characteristics of the EMP environment. The paper is based on an inductive theory-building process initiated from a case study in the field of emergency medical services. The development of the suggested performance improvement approach triggered from an exhaustive analysis of a process involved and an exploratory review of the existing improvement approaches available. The process of concern can be described as a specialized transportation process, where human lives are at risk. Its characteristics led to a natural application of Lean transportation. The results include, a novel approach for improving the agility and efficient EMS processes. This is validated with an application for improving ambulance response times and turnaround times of the Red Cross operations located in Monterrey, Mexico. The approach proved to be an integrated scheme for identifying waste opportunities at a systems level. This characteristic is important to let operations management prioritize improvement efforts in a limited budget situation. This work suggests the application of the emerging Lean transportation approach for increasing the agility performance of EMS processes.     

From Students to Scholars: Undergraduate Research and the Importance of Regional Conferences

This paper highlights the benefits of regional conferences to the development of undergraduate scholars. Presenting at such conferences helps undergraduates see their work in a different light—as scholarship and not simply coursework. Furthermore, the experience speeds their transformation from consumers to producers of knowledge.     

Bayesian analysis of head and neck cancer data using generalized inverse Lindley stress–strength reliability model

In this article, we present the analysis of head and neck cancer data using generalized inverse Lindley stress–strength reliability model. We propose Bayes estimators for estimating P(X > Y), when X and Y represent survival times of two groups of cancer patients observed under different therapies. The X and Y are assumed to be independent generalized inverse Lindley random variables with common shape parameter. Bayes estimators are obtained under the considerations of symmetric and asymmetric loss functions assuming independent gamma priors. Since posterior becomes complex and does not possess closed form expressions for Bayes estimators, Lindley’s approximation and Markov Chain Monte Carlo techniques are utilized for Bayesian computation. An extensive simulation experiment is carried out to compare the performances of Bayes estimators with the maximum likelihood estimators on the basis of simulated risks. Asymptotic, bootstrap, and Bayesian credible intervals are also computed for the P(X > Y).     

Green and lean: a Gemba–Kaizen model for sustainability enhancement

Abstract

Despite the encouraging results obtained from the application of Green Lean, organizations have found the integration of Green and Lean, and their implementation as an integrated approach, challenging. This paper therefore presents a model for integrating Lean and Green based on the Gemba-Kaizen approach. The proposed model was developed on the basis of a through literature review on Gemba and Kaizen, conducted on peer reviewed journal articles and pragmatic books, and the more than 40 years of accumulated experience of the authors as academics, researchers, industrialists and consultants. The model was validated through two cases study in the aerospace and automotive industries. The results showed that the proposed model helped the case organizations to reduce the consumption of resources and improve their environmental performance. The proposed model can be the basis for further research on Lean and Green, contributing to help organizations to improve their sustainability performance.     

Knowledge management for sustainability in operations

Abstract

The purpose of this paper is to examine the effect of Knowledge Management (KM) as a platform to enable sustainability in firms’ operations and to provide recommendations for managers to integrate sustainable operations into their business strategies. The urgency to create and implement sustainable operations is also argued. The conceptual framework is based on the hypothesis that KM contributes to the achievement of more suitable operations. To test this hypothesis, a model of structural equations was developed with data collected from 345 SMEs. Empirical evidence supported the hypothesis, indicating that KM represents an important alternative to implementing sustainability. The results suggest that managers need to implent KM, as they will enable a better understanding and awareness regarding the global dangerous impacts from unsustainable operations mainly focused on sales and cost reduction. For this reason, this research provides evidence that KM offers an alternative impulse on the quest for more sustainable operations.