Abstract

Abstract

Abstract
This paper presents a binary acceleration approach based on extending a General Purpose Processor (GPP) with a Reconfigurable Processing Unit (RPU), both sharing an external data memory. In this approach repeating sequences of GPP instructions are migrated to the RPU. The RPU resources are selected and organized off-line using execution trace information. The RPU core is composed of Functional Units (FUs) that correspond to single CPU instructions. The FUs are arranged in stages of mutually independent operations. The RPU can enable several stages in tandem, depending on the data dependencies. External data memory accesses are handled by a configurable dual-port cache. A prototype implementation of the architecture on a Spartan-6 FPGA was validated with 12 benchmarks and achieved an overall geometric mean speedup of 1.91x.

Abstract
Existing adaptive educational hypermedia systems have been using learning resources sequencing approaches in order to enrich the learning experience. In this context, educational resources, either expository or evaluative, play a central role. However, there is a lack of tools that support sequencing essentially due to the fact that existing specifications are complex. This paper presents Seqins as a sequencing tool of digital educational resources. Seqins includes a simple and flexible sequencing model that will foster heterogeneous students to learn at different rhythms. The tool communicates through the IMS Learning Tools Interoperability specification with a plethora of e-learning systems such as learning management systems, repositories, authoring and automatic evaluation systems. In order to validate Seqins we integrate it in an e-learning Ensemble framework instance for the computer programming learning domain.

Abstract
Flexibility requirements can appear in the middle of a software development, perceived by several client requests to change the application. A flexible domain model, usually implemented with using the adaptive object model (AOM) architectural style, required custom-made components to handle the current implementation of the domain entities. The problem is that by evolving an AOM model, the components need to be evolved as well, which generates constant rework. This work studied the possible AOM evolution paths, in order to provide support in the components for model changing. An evolution of the Esfinge AOM RoleMapper framework were developed to provide this functionality, allowing AOM models in different stages to be mapped to a single structure. The study was evaluated using a set of tests that were applied in each possible structure for the model.

Abstract
Industrial automation relies on PLC's to perform real-time critical tasks. These tasks are commonly implemented using IEC 61131-3 and tend to be very complex due to the current evolution of microprocessor capabilities. This complexity causes testing to be considered a very difficult task and the scope to be reduced to minimize effort. The application of automatic calibration techniques could allow the identification of optimal or near optimal solutions for the set of inputs to allow a better test coverage and simulation accuracy. This paper reviews current automatic simulation calibration methodologies and provides a description of an experiment of the application of search-based metaheuristics to IEC 61131-3 implemented algorithms in the context of power systems automation.