Formalizing process-based risk with Value-Focused Process Engineering

Following calls to advance the integration of risk and business process modeling paradigms, this paper formalizes the process of incorporating risk into business process models through the principles of Value-Focused Process Engineering (VFPE). In doing so, the paper aims to extend the existing VFPE modeling notation to reflect a set of necessary constructs required to adequately represent risk in goal-oriented business-process models. The extended set of constructs is proposed to support a formal systems view of process-based risk. Process-based risk is formalized on the one hand, as a product of complex interactions between activity-based elements, and on the other hand, as a natural component of the value creation mechanism of an elementary function or a complex process. The proposed risk-aware VFPE formalism also formulates rules for decomposing risk in process models according to the organizational values, thereby enabling better risk visibility, reducing process complexity, and ensuring continuity of business processes.     

Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data

The simulation of gross primary production (GPP) at various spatial and temporal scales remains a major challenge for quantifying the global carbon cycle. We developed a light use efficiency model, called EC-LUE, driven by only four variables: normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and the Bowen ratio of sensible to latent heat flux. The EC-LUE model may have the most potential to adequately address the spatial and temporal dynamics of GPP because its parameters (i.e., the potential light use efficiency and optimal plant growth temperature) are invariant across the various land cover types. However, the application of the previous EC-LUE model was hampered by poor prediction of Bowen ratio at the large spatial scale. In this study, we substituted the Bowen ratio with the ratio of evapotranspiration (ET) to net radiation, and revised the RS-PM (Remote Sensing-Penman Monteith) model for quantifying ET. Fifty-four eddy covariance towers, including various ecosystem types, were selected to calibrate and validate the revised RS-PM and EC-LUE models. The revised RS-PM model explained 82% and 68% of the observed variations of ET for all the calibration and validation sites, respectively. Using estimated ET as input, the EC-LUE model performed well in calibration and validation sites, explaining 75% and 61% of the observed GPP variation for calibration and validation sites respectively.Global patterns of ET and GPP at a spatial resolution of 0.5° latitude by 0.6° longitude during the years 2000-2003 were determined using the global MERRA dataset (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate Resolution Imaging Spectroradiometer). The global estimates of ET and GPP agreed well with the other global models from the literature, with the highest ET and GPP over tropical forests and the lowest values in dry and high latitude areas. However, comparisons with observed GPP at eddy flux towers showed significant underestimation of ET and GPP due to lower net radiation of MERRA dataset. Applying a procedure to correct the systematic errors of global meteorological data would improve global estimates of GPP and ET. The revised RS-PM and EC-LUE models will provide the alternative approaches making it possible to map ET and GPP over large areas because (1) the model parameters are invariant across various land cover types and (2) all driving forces of the models may be derived from remote sensing data or existing climate observation networks.     

Experimental evaluation of pheromone models in ACOPlan

In this paper the system ACOPlan for planning with non uniform action cost is introduced and analyzed. ACOPlan is a planner based on the ant colony optimization framework, in which a colony of planning ants searches for near optimal solution plans with respect to an overall plan cost metric. This approach is motivated by the strong similarity between the process used by artificial ants to build solutions and the methods used by state?Cbased planners to search solution plans. Planning ants perform a stochastic and heuristic based search by interacting through a pheromone model. The proposed heuristic and pheromone models are presented and compared through systematic experiments on benchmark planning domains. Experiments are also provided to compare the quality of ACOPlan solution plans with respect to state of the art satisficing planners. The analysis of the results confirm the good performance of the Action?CAction pheromone model and points out the promising performance of the novel Fuzzy?CLevel?CAction pheromone model. The analysis also suggests general principles for designing performant pheromone models for planning and further extensions of ACOPlan to other optimization models.     

Maximum Likelihood Estimation of the Cox–Ingersoll–Ross Model Using Particle Filters

This paper shows how to build in a computationally efficient way a maximum simulated likelihood procedure to estimate the Cox–Ingersoll–Ross model from multivariate time series. The advantage of this estimator is that it takes into account the exact likelihood function while avoiding the huge computational burden associated with MCMC methods and without the ad hoc assumption that certain bond yields are measured without error. The proposed methodology is implemented and tested on simulated data. For realistic parameter values the estimator seems to have good small sample properties, compared to the popular quasi maximum likelihood approach, even using moderate simulation sizes. The effect of simulation errors does not seem to undermine the estimation procedure.     

A coarse-grain reconfigurable architecture for multimedia applications supporting subword and floating-point calculations

Signal processors exploiting ASIC acceleration suffer from sky-rocketing manufacturing costs and long design cycles. FPGA-based systems provide a programmable alternative for exploiting computation parallelism, but the flexibility they provide is not as high as in processor-oriented architectures: HDL or C-to-HDL flows still require specific expertise and a hardware knowledge background. On the other hand, the large size of the configuration bitstream and the inherent complexity of FPGA devices make their dynamic reconfiguration not a very viable approach. Coarse-grained reconfigurable architectures (CGRAs) are an appealing solution but they pose implementation problems and tend to be application specific. This paper presents a scalable CGRA which eases the implementation of algorithms on field programmable gate array (FPGA) platforms. This design option is based on two levels of programmability: it takes advantage of performance and reliability provided by state-of-the-art FPGA technology, and at the same time it provides the user with flexibility, performance and ease of reconfiguration typical of standard CGRAs. The basic cell template provides advanced features such as sub-word SIMD integer and floating-point computation capabilities, as well as saturating arithmetic. Multiple reconfiguration contexts and partial run-time reconfiguration capabilities are provided, tackling this way the problem of high reconfiguration overhead typical of FPGAs. Selected instances of the proposed architecture have been implemented on an Altera Stratix II EP2S180 FPGA. On this system, we mapped some common DSP, image processing, 3D graphics and audio compression algorithms in order to validate our approach and to demonstrate its effectiveness by benchmarking the benefits achieved.     

Network Awareness of P2P Live Streaming Applications: A Measurement Study

Early P2P-TV systems have already attracted millions of users, and many new commercial solutions are entering this market. Little information is however available about how these systems work, due to their closed and proprietary design. In this paper, we present large scale experiments to compare three of the most successful P2P-TV systems, namely PPLive, SopCast and TVAnts. Our goal is to assess what level of "network awareness" has been embedded in the applications. We first define a general framework to quantify which network layer parameters leverage application choices, i.e., what parameters mainly drive the peer selection and data exchange. We then apply the methodology to a large dataset, collected during a number of experiments where we deployed about 40 peers in several European countries. From analysis of the dataset, we observe that TVAnts and PPLive exhibit a mild preference to exchange data among peers in the same autonomous system the peer belongs to, while this clustering effect is less intense in SopCast. However, no preference versus country, subnet or hop count is shown. Therefore, we believe that next-generation P2P live streaming applications definitively need to improve the level of network-awareness, so to better localize the traffic in the network and thus increase their network-friendliness as well.     

A silicone-based microfluidic chip grafted with carboxyl functionalized hyperbranched polyglycerols for selective protein capture

A poly(dimethylsiloxane) (PDMS)-based functional microfluidic device containing a charged matrix of PDMS pillar arrays grafted with hyperbranched polyglycerols (HPGs) was developed. Samples of PDMS were modified with allylamine plasma to form amine groups on the surface prior to the covalent grafting of succinimdyl ester-functionalized HPGs. The anionic functionality of the PDMS channel matrices was developed by altering the number of carboxyl groups present on the HPGs. The grafting of HPGs onto PDMS plates was investigated via contact angle measurement and attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), while the grafting of the inside channel was investigated by electroosmotic flow (EOF) measurements. The charge density on grafted HPG was optimized to minimize the nonspecific protein adsorption and increase the selective capture of positively charged proteins. A proof-of-concept device was fabricated on PDMS and demonstrated that the device selectively captures positively charged protein (avidin) from a mixture of bovine serum albumin (BSA)-avidin at pH 7.4 in phosphate buffered saline (PBS). In order to increase the capture efficiency of the proteins in this PDMS-based device, pillar arrays have been fabricated within the channel. As a demonstration, the new device separated two proteins with an avidin capture efficiency of 100 ± 2.95% per 3 min from a 0.02 mg/ml protein solution (avidin:BSA wt ratio: 1:1). This new microfluidic-based device shows a great deal of promise as a tool for protein capture and analysis.     

The MORPHEUS Heterogeneous Dynamically Reconfigurable Platform

Reconfigurable computing offers a wide range of low cost and efficient solutions for embedded systems. The proper choice of the reconfigurable device, the granularity of its processing elements and its memory architecture highly depend on the type of application and their data flow. Existing solutions either offer fine grain FPGAs, which rely on a hardware synthesis flow and offer the maximum degree of flexibility, or coarser grain solutions, which are usually more suitable for a particular type of data flow and applications. In this paper, we present the MORPHEUS architecture, a versatile reconfigurable heterogeneous System-on-Chip targeting streaming applications. The presented architecture exploits different reconfigurable technologies at several computation granularities that efficiently address the different applications needs. In order to efficiently exploit the presented architecture, we implemented a complete software solution to map C applications to the reconfigurable architecture. In this paper, we describe the complete toolset and provide concrete use cases of the architecture.     

Path dependent stochastic models to detect planned and actual technology use: A case study of OpenOffice

Context

Adopting IT innovation in organizations is a complex decision process driven by technical, social and economic issues. Thus, those organizations that decide to adopt innovation take a decision of uncertain success of implementation, as the actual use of a new technology might not be the one expected. The misalignment between planned and effective use of innovation is called assimilation gap.

Objective

This research aims at defining a quantitative instrument for measuring the assimilation gap and applying it to the case of the adoption of OSS.

Method

In this paper, we use the theory of path dependence and increasing returns of Arthur. In particular, we model the use of software applications (planned or actual) by stochastic processes defined by the daily amounts of files created with the applications. We quantify the assimilation gap by comparing the resulting models by measures of proximity.

Results

We apply and validate our method to a real case study of introduction of OpenOffice. We have found a gap between the planned and the effective use despite well-defined directives to use the new OS technology. These findings suggest a need of strategy re-calibration that takes into account environmental factors and individual attitudes.

Conclusions

The theory of path dependence is a valid instrument to model the assimilation gap provided information on strategy toward innovation and quantitative data on actual use are available.