Abstract
In this paper we present a multiyear dynamic transmission expansion planning formulation considering criteria related with reliability and investment and operation costs. This problem is solved using an interactive method that starts at a non-dominated solution identified by the epsilon-constraint method, in which all objectives except one are converted in constraints using aspiration levels. Afterwards, the decision maker can modify the initial aspiration levels to improve some specific criteria. As a final result, the algorithm determines long term marginal prices, reflecting both investment and operation costs. These prices are well suited to tariff the use of networks as they transmit economic signals to users while addressing the Revenue Reconciliation Problem, typical when using short term approaches. The described approach was used to identify the most adequate 6 year expansion plan for the Portuguese transmission system, the long term marginal prices and the percentage of cost recovery.

Abstract
Java applets run on a Virtual Machine that checks code's integrity and correctness before execution using a module called Bytecode Verifier. Java Card technology allows Java applets to run on smart cards. Large memory space requirements of the verification process do not allow the implementation of a Bytecode Verifier embedded in the Java Card Virtual Machine. To address this feasibility problem, we propose a modified verification algorithm that optimizes the use of system memory. The algorithm, inspired to compilers' techniques, partitions the code of the methods into control regions. In this way data structures can be dynamically allocated and the verification process can be applied locally to a subset of instructions.

Abstract
Several works on grid computing have been proposed in the last years. However, most of them, including available software, can not deal properly with some issues related to control of applications that spread a very large number of tasks across the grid network. This work presents a step toward solving the problem of controlling such applications. We propose and discuss an architectural model called GRAND (Grid Robust ApplicatioN Deployment) based on partitioning and hierarchical submission and control of such applications. The main contribution of our model is to be able to control the execution of a huge number of distributed tasks while preserving data locality and reducing the load of the submit machines. We propose a taxonomy to classify application models to run in grid environments and partitioning methods. We also present our application description language GRID-ADL. Copyright 2004 ACM.

Abstract
This paper describes an experimental study that aimed at determining the mandibular strains provoked by impact loads on conventional and non-conventional dental implant systems. The novel implant differs from typical commercial designs because it comprises an elastomeric material barrier (stress shock absorber) interposed between the implant and an artificial crown. A dried implanted cadaveric mandible with strain gauges placed at the inner and outer surfaces in the direction of the implant axis was used. The implants were loaded dynamically and uniaxial strains recorded. Overall, the results showed that an interposing flexible material between the crown and the top surface of the implant attenuates the load, avoiding high peak loads, which can occasionally occur from non-physiological occlusion loads that can be transferred to the surrounding bone tissue.

Abstract
Collecting and mining clickstream data from c-commerce sites has become increasingly important for marketing, advertising, and traffic analysis activities. Organizations are promoting many initiatives concerning user's navigation pattern discovery, in order to implement better sites, more functional and close to customers' needs. Basically, the main idea is to provide more quality of attendance in their sites, and, consequently, get more profitability. However, clickstream processing is not a simple task. The sequences of clicks are very difficult to handle using conventional techniques, essentially due to their diversity and nature. They include a lot of aspects that reveal the multidimensional perspective of web data. OLAP technology provides today the means and techniques to represent, store and analyse such kinds of multidimensional data. However, it does not offer discovery driven analysis to support traversal pattern identification processes on web sites. Mining traversal pattern techniques can be applied in conjunction with OLAP as an integrated alternative for understanding those particular sequences of clicks. In this paper we present an integrated OLAP and mining approach specially conceived for exploring user navigation patterns based on clickstreams. We also describe the multidimensional structure provided for modelling click sequences and the OLAP operations and mining techniques that can be pushed over data cubes to bring up navigation patterns.

Abstract