An empirical study of information technology enabled business process redesign and corporate competitive strategy

Business process redesign (BPR) has been widely touted as a means for leveraging the power of information technology to change business processes radically, resulting in substantial improvements in organizational effectiveness and efficiency. This study represents an early attempt at examining the strategic nature of the phenomenon. Because BPR is radical change and has the ability to alter both the competitive and operational nature of the corporation, it is critical that BPR be coordinated with corporate strategy. Through a survey of information system executives, the relationships between corporate competitive strategy and three types of BPR – intrafunctional, interfunctional and interorganizational – were examined. It was found that organizations following a cost strategy tended to do more BPR projects on interfunctional processes. Furthermore, the positive effect of a cost strategy on interfunctional BPR was found to be strengthened by the degree of integration of IS and business planning. It was also found that while interorganizational BPR was not related to a specific strategy, it was strongly related directly with IS–business planning integration.     

Optimal capacity placement for path restoration in STM or ATMmesh-survivable networks

The total transmission capacity required by a transport network to satisfy demand and protect it from failures contributes significantly to its cost, especially in long-haul networks. Previously, the spare capacity of a network with a given set of working span sizes has been optimized to facilitate span restoration. Path restorable networks can, however, be even more efficient by defining the restoration problem from an end to end rerouting viewpoint. We provide a method for capacity optimization of path restorable networks which is applicable to both synchronous transfer mode (STM) and asynchronous transfer mode (ATM) virtual path (VP)-based restoration. Lower bounds on spare capacity requirements in span and path restorable networks are first compared, followed by an integer program formulation based on flow constraints which solves the spare and/or working capacity placement problem in either span or path restorable networks. The benefits of path and span restoration, and of jointly optimizing working path routing and spare capacity placement, are then analyzed     

Pharmacology of ATP-sensitive potassium channel (KATP) openers in models of myocardial ischemia and reperfusion

Cancer cells release various antigens, some of which appear in the urine. Oral autourotherapy is suggested as a new treatment modality for cancer patients. It will provide the intestinal lymphatic system with the many tumor antigens against which antibodies may be produced. These antibodies may be pierced through the blood stream and attack the tumor and its cells.     

Age effects in coding tasks: Componential analysis and test of the sensory deficit hypothesis.

Multiple forms of a symbol-digit substitution task were used to provide a componential analysis of age differences in coding task performance. The results demonstrated age differences in feature encoding, memory, and visual search. A 2nd experiment was conducted with young adults to investigate a sensory deficit as a locus of age differences. The spatial contrast sensitivity deficit of older adults was simulated on forms by applying a digital filter. Persons in the age-simulated contrast condition performed worse than those in the normal contrast condition. The stimulus degradation effect was linked to visual search speed. The study illustrates the utility of componential analysis and offers direct support for the hypothesis that sensory deficits affect performance on tasks used to assess intelligence (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Availability analysis of span-restorable mesh networks

The most common aim in designing a survivable network is to achieve restorability against all single span failures, with a minimal investment in spare capacity. This leaves dual-failure situations as the main factor to consider in quantifying how the availability of services benefit from the investment in restorability. We approach the question in part with a theoretical framework and in part with a series of computational routing trials. The computational part of the analysis includes all details of graph topology, capacity distribution, and the details of the restoration process, effects that were generally subject to significant approximations in prior work. The main finding is that a span-restorable mesh network can be extremely robust under dual-failure events against which they are not specifically designed. In a modular-capacity environment, an adaptive restoration process was found to restore as much as 95% of failed capacity on average over all dual-failure scenarios, even though the network was designed with minimal spare capacity to assure only single-failure restorability. The results also imply that for a priority service class, mesh networks could provide even higher availability than dedicated 1+1 APS. This is because there are almost no dual-failure scenarios for which some partial restoration level is not possible, whereas with 1+1 APS (or rings) there are an assured number of dual-failure scenarios for which the path restorability is zero. Results suggest conservatively that 20% or more of the paths in a mesh network could enjoy this ultra-high availability service by assigning fractional recovery capacity preferentially to those paths upon a dual failure scenario     

Information technology innovations: general diffusion patterns andits relationships to innovation characteristics

While many scholars of organizational innovations have examined characteristics of innovations such as relative advantage and complexity and how they facilitate the adoption of an innovation by organizations, others have used mathematical models to fit diffusion patterns. In this study, the authors attempt to integrate these two areas of inquiry and explore the possibilities to predict diffusion patterns based on characteristics of the innovation and the adopting entities. Based on a cross-sectional sample of 313 large American firms, 20 information technology (IT) innovations were examined and their diffusion patterns assessed with respect to models that espoused internal and external influence. The mixed influence model (Bass model) was chosen as a robust common representation for the set of diffusion patterns. However, the external influence as represented by the coefficient of innovation was found to be extremely small and the internal influence dominates for all innovations. The other two parameters of the model, the saturation level and the coefficient of imitation, which represents internal influence, were then used to perform a cluster analysis. Five clusters of technologies emerged, and the potential relationships between their innovation characteristics and diffusion patterns were explored. Rigorous examination of these potential relationships by future researchers may result in practical methods for predicting patterns of IT innovation diffusion based on innovation and technology characteristics     

A comparison of statistical relational learning and graph neural networks for aggregate graph queries

Statistical relational learning (SRL) and graph neural networks (GNNs) are two powerful approaches for learning and inference over graphs. Typically, they are evaluated in terms of simple metrics such as accuracy over individual node labels. Complex aggregate graph queries (AGQ) involving multiple nodes, edges, and labels are common in the graph mining community and are used to estimate important network properties such as social cohesion and influence. While graph mining algorithms support AGQs, they typically do not take into account uncertainty, or when they do, make simplifying assumptions and do not build full probabilistic models. In this paper, we examine the performance of SRL and GNNs on AGQs over graphs with partially observed node labels. We show that, not surprisingly, inferring the unobserved node labels as a first step and then evaluating the queries on the fully observed graph can lead to sub-optimal estimates, and that a better approach is to compute these queries as an expectation under the joint distribution. We propose a sampling framework to tractably compute the expected values of AGQs. Motivated by the analysis of subgroup cohesion in social networks, we propose a suite of AGQs that estimate the community structure in graphs. In our empirical evaluation, we show that by estimating these queries as an expectation, SRL-based approaches yield up to a 50-fold reduction in average error when compared to existing GNN-based approaches.

     

Proton Conductivity Measurements in Yttrium Barium Cerate by Impedance Spectroscopy

Proton-conducting solid-electrolyte perovskite ceramics based on acceptor-doped barium and strontium cerates have become the focus of extensive investigations as candidate materials for fuel cells that operate at moderate temperatures. To assess the suitability of a material for this application, it is necessary that bulk electrolyte conductivity be measured at the operating temperature. However, very little reliable published conductivity data exist above 600°C. Protonic conductivity in yttrium-doped barium cerate has been observed to be less at high temperatures than would be expected, based on the activation energy and preexponential for hydrogen transport at temperatures <300°C. Conductivity data obtained from impedance spectroscopy on BaCe_0.9Y_0.1O_3–α over the extended temperature range of 100°–900°C are presented. An Arrhenius plot of the data shows two distinct linear regions, suggesting that two different rate-limiting processes occur in series with a break-over transition at ∼250°C. The decrease in conductivity is apparently not due to dehydration. An activation energy for protonic transport of 0.26 eV, about one-half of the low-temperature value, is proposed, based on curve fitting of the high-temperature data.     

Comparison of two scaling approaches for the development of biomechanical multi-body human models

Dimensional scaling approaches are widely used to develop multi-body human models in injury biomechanics research. Given the limited experimental data for any particular anthropometry, a validated model can be scaled to different sizes to reflect the biological variance of population and used to characterize the human response. This paper compares two scaling approaches at the whole-body level: one is the conventional mass-based scaling approach which assumes geometric similarity; the other is the structure-based approach which assumes additional structural similarity by using idealized mechanical models to account for the specific anatomy and expected loading conditions. Given the use of exterior body dimensions and a uniform Young’s modulus, the two approaches showed close values of the scaling factors for most body regions, with 1.5 % difference on force scaling factors and 13.5 % difference on moment scaling factors, on average. One exception was on the thoracic modeling, with 19.3 % difference on the scaling factor of the deflection. Two 6-year-old child models were generated from a baseline adult model as application example and were evaluated using recent biomechanical data from cadaveric pediatric experiments. The scaled models predicted similar impact responses of the thorax and lower extremity, which were within the experimental corridors; and suggested further consideration of age-specific structural change of the pelvis. Towards improved scaling methods to develop biofidelic human models, this comparative analysis suggests further investigation on interior anatomical geometry and detailed biological material properties associated with the demographic range of the population.     

Bioenergy,food security and poverty reduction: trade-offs and synergies along the water–energy–food security nexus

This article provides a review of trade-offs and synergies of bioenergy within the water–energy–food security nexus, with emphasis on developing countries. It explores the links of bioenergy with food security, poverty reduction, environmental sustainability, health, and gender equity. It concludes that applying the nexus perspective to analyses of bioenergy widens the scope for achieving multiple-win outcomes along the above aspects.