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.     

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.     

Using frameworks to develop a distributed conferencing system: an experience report

Application frameworks are a powerful means to reduce software development costs while improving quality. However, at the same time they are difficult to select and understand, as well as hard to learn, use, and debug effectively and efficiently. In this paper we report the story of eConference, a distributed conferencing system that was developed as part of a broader research effort. Here we discuss the lessons learned from the evolution of our conferencing tool over four generations, which have been necessary to find good frameworks and build a flexible distributed tool. Copyright © 2009 John Wiley & Sons, Ltd.     

Evaluating the impact of smart technologies on harbor’s logistics via BPMN modeling and simulation

A smart Information and Communication Technology (ICT) enables a synchronized interplay of different key factors, aligning infrastructures, consumers, and governmental policy-making needs. In the harbor’s logistics context, smart ICT has been driving a multi-year wave of growth. Although there is a standalone value in the technological innovation of a task, the impact of a new smart technology is unknown without quantitative analysis methods on the end-to-end process. In this paper, we first present a review of the smart ICT for marine container terminals, and then we propose to evaluate the impact of such smart ICT via business process model and notation (BPMN) modeling and simulation. The proposed approach is discussed in a real-world modeling and simulation analysis, made on a pilot terminal of the Port of Leghorn (Italy).     

Development and applications of surface-activated chemical ionization

This review regards the recently developed ionization source named surface-activated chemical ionization (SACI) that employs an interaction with a surface placed at low voltage for the activation of the ionization of sample molecules to increase the sensitivity in the analysis of various compounds of biological and clinical interest. These results are due to the strong chemical noise decrease and the increase of ionization efficiency. This ionization source has been employed for the analysis of various compounds of different molecular mass and polarity (addicted and pharmaceutical drugs, amino acids, steroids, peptides, and proteins). The SACI development theoretical mechanism, benefits, disadvantages, applications, and future developments are reported and discussed.     

An improved correlation for the calculation of liquid thermal conductivity

Eighteen correlations appearing in the literature for the prediction of thermal conductivity, , of liquids are critically analyzed, and their reliability is checked using coherent input data and selected experimental values. The best results are obtained using the Reid, Sherwood, and Prausnitz correlation with a mean deviation of about 8% between predicted and experimental values. An improved correlation is proposed starting from the Viswanath equation, chosen because of its simplicity and convenience. The values of thermal conductivity obtained by this new correlation agree with the experimental values within 1%.     

Definition of Risk Indicators for Reservoirs Management Optimization

An alternative procedure for drought risk assessment and for the mitigation of drought risk is proposed in the paper. An analysis of the relationship between failure of water supply systems and reservoir volumes for the urban area of Firenze in central Tuscany, in central Italy, is performed. Long term simulations are carried out using the software package WEAP. A simplified model of the water resources system is built to assess the threshold values and the management rules. The probability to have definite degree of shortage in the water supply system is evaluated in function of the volume stored in the reservoir at the beginning of the month with Monte Carlo simulations. The reservoir levels and volumes are simulated using time series of the period 1970–2005. Four scenarios (i.e. normal, pre-alert, alert and emergency) associated with different levels of severity of drought are defined. Threshold values are identified considering the probability to assure a given fraction of the demand in a certain time horizon, and are calibrated with an optimization method, which try to minimize the water shortages, especially the heavier. The critical situations are assessed month by month in order to evaluate optimal management rules during the year and avoid conditions of total water shortage.