Table 6 Generalised properties of Utsira caprocks, based on analysis of cuttings (page 79)

Executive Summary: Carbon dioxide capture and storage (CCS) is one option for mitigating atmospheric emissions of carbon dioxide and thereby contributes in actions for stabilization of atmospheric greenhouse gas concentrations. The Bellona Foundation is striving to achieve wide implementation of carbon dioxide (CO2) capture and storage both in Norway and internationally. Bellona considers CCS as the only viable large scale option to close the gap between energy production and demand in an environmentally sound way, thereby ensuring that climate changes and acidification of the oceans due to increased CO2 concentrations in the atmosphere will be stabilised. ff

Is FTA/EPA effective for a developing country to attract FDI? : simulation analysis based on an extended knowledge-capital model

To prepare an answer to the question of how a developing country can attract FDI, this paper explored the factors and policies that may help bring FDI into a developing country by utilizing an extended version of the knowledge-capital model. With a special focus on the effects of FTAs/EPAs between market countries and developing countries, simulations with the model revealed the following: (1) Although FTA/EPA generally ends to increase FDI to a developing country, the possibility of improving welfare through increased demand for skilled and unskilled labor becomes higher as the size of the country declines; (2) Because the additional implementation of cost-saving policies to reduce firm-type/trade-link specific fixed costs ends to depreciate the price of skilled labor by saving its input, a developing country, which is extremely scarce in skilled labor, is better off avoiding the additional option; (3) If a country hopes to enjoy larger welfare gains with EPA, efforts to increase skilled labor in the country, such as investing in education, may be beneficial.

Simulation analysis of the EU ELV/RoHS directives based on an applied general equilibrium model with Melitz-type trade specification

This paper explores the potential usefulness of an AGE model with the Melitz-type trade specification to assess economic effects of technical regulations, taking the case of the EU ELV/RoHS directives as an example. Simulation experiments reveal that: (1) raising the fixed exporting cost to make sales in the EU market brings results that exports of the targeted commodities (motor vehicles and parts for ELV and electronic equipment for RoHS) to the EU from outside regions/countries expand while the domestic trade in the EU shrinks when the importer's preference for variety (PfV) is not strong; (2) if the PfV is not strong, policy changes that may bring reduction in the number of firms enable survived producers with high productivity to expand production to be large-scale mass producers fully enjoying the fruit of economies of scale; and (3) When the strength of the importer's PfV is changed from zero to unity, there is the value that totally changes simulation results and their interpretations.

Video analysis based vehicle detection and tracking using an MCMC sampling framework

This article presents a probabilistic method for vehicle detection and tracking through the analysis of monocular images obtained from a vehicle-mounted camera. The method is designed to address the main shortcomings of traditional particle filtering approaches, namely Bayesian methods based on importance sampling, for use in traffic environments. These methods do not scale well when the dimensionality of the feature space grows, which creates significant limitations when tracking multiple objects. Alternatively, the proposed method is based on a Markov chain Monte Carlo (MCMC) approach, which allows efficient sampling of the feature space. The method involves important contributions in both the motion and the observation models of the tracker. Indeed, as opposed to particle filter-based tracking methods in the literature, which typically resort to observation models based on appearance or template matching, in this study a likelihood model that combines appearance analysis with information from motion parallax is introduced. Regarding the motion model, a new interaction treatment is defined based on Markov random fields (MRF) that allows for the handling of possible inter-dependencies in vehicle trajectories. As for vehicle detection, the method relies on a supervised classification stage using support vector machines (SVM). The contribution in this field is twofold. First, a new descriptor based on the analysis of gradient orientations in concentric rectangles is dened. This descriptor involves a much smaller feature space compared to traditional descriptors, which are too costly for real-time applications. Second, a new vehicle image database is generated to train the SVM and made public. The proposed vehicle detection and tracking method is proven to outperform existing methods and to successfully handle challenging situations in the test sequences.