Modelling co-operation in the design of knowledge production systems: The Made In'Coop method

This paper presents the latest developments of the MadeIn 'Coop method for modelling the human-machine and human-human co-operation process, and an application of this method for the design of a more co-operative version of the C³I System CHEOPS. We first consider that the design of software systems for organizations is tied more and more to the perspective of compound Knowledge Production Systems that link humans and machines engaged in a co-operative problem solving process. After exposing the four principles upon which MadeIn 'Coop rests for modelling co-operation, we present an artificial problem solving dialogue between CHEOPS and its users. Consistent with the Group Cognitive Processes Theory framework, we propose a dialogue analysis according to two complimentary points of view: the Collective Problem Solving model, and the Coordination model. This analysis should help system designers to identify new system functionalities to assist problem solving.(C³I) Command Control Communication Intelligence Systems     

Efficient on-line signature recognition based on multi-section vector quantization

This paper proposes a multi-section vector quantization approach for on-line signature recognition. We have used a database of 330 users which includes 25 skilled forgeries performed by 5 different impostors. This database is larger than those typically used in the literature. Nevertheless, we also provide results from the SVC database. Our proposed system obtains similar results as the state-of-the-art online signature recognition algorithm, Dynamic Time Warping, with a reduced computational requirement, around 47 times lower. In addition, our system improves the database storage requirements due to vector compression, and is more privacy-friendly because it is not possible to recover the original signature using the codebooks. Experimental results reveal that our proposed multi-section vector quantization achieves a 98% identification rate, minimum Detection Cost Function value equal to 2.29% for random forgeries and 7.75% for skilled forgeries.     

Real-time hierarchical stereo Visual SLAM in large-scale environments

In this paper we present a new real-time hierarchical (topological/metric) Visual SLAM system focusing on the localization of a vehicle in large-scale outdoor urban environments. It is exclusively based on the visual information provided by a cheap wide-angle stereo camera. Our approach divides the whole map into local sub-maps identified by the so-called fingerprints (vehicle poses). At the sub-map level (low level SLAM), 3D sequential mapping of natural landmarks and the robot location/orientation are obtained using a top-down Bayesian method to model the dynamic behavior. A higher topological level (high level SLAM) based on fingerprints has been added to reduce the global accumulated drift, keeping real-time constraints. Using this hierarchical strategy, we keep the local consistency of the metric sub-maps, by mean of the EKF, and global consistency by using the topological map and the MultiLevel Relaxation (MLR) algorithm. Some experimental results for different large-scale outdoor environments are presented, showing an almost constant processing time.     

A scalable organization for distributed directories

Although directory-based cache-coherence protocols are the best choice when designing chip multiprocessors with tens of cores on-chip, the memory overhead introduced by the directory structure may not scale gracefully with the number of cores. Many approaches aimed at improving the scalability of directories have been proposed. However, they do not bring perfect scalability and usually reduce the directory memory overhead by compressing coherence information, which in turn results in extra unnecessary coherence messages and, therefore, wasted energy and some performance degradation. In this work, we present a distributed directory organization based on duplicate tags for tiled CMP architectures whose size is independent on the number of tiles of the system up to a certain number of tiles. We demonstrate that this number of tiles corresponds to the number of sets in the private caches. Additionally, we show that the area overhead of the proposed directory structure is 0.56% with respect to the on-chip data caches. Moreover, the proposed directory structure keeps the same information than a non-scalable full-map directory. Finally, we propose a mechanism that takes advantage of this directory organization to remove the network traffic caused by replacements. This mechanism reduces total traffic by 15% for a 16-core configuration compared to a traditional directory-based protocol.     

Designing adaptive learning itineraries using features modelling and swarm intelligence

In this paper, Bayesian network (BN) and ant colony optimization (ACO) techniques are combined in order to find the best path through a graph representing all available itineraries to acquire a professional competence. The combination of these methods allows us to design a dynamic learning path, useful in a rapidly changing world. One of the most important advances in this work, apart from the variable amount of pheromones, is the automatic processing of the learning graph. This processing is carried out by the learning management system and helps towards understanding the learning process as a competence-oriented itinerary instead of a stand-alone course. The amount of pheromones is calculated by taking into account the results acquired in the last completed course in relation to the minimum score required and by feeding this into the learning tree in order to obtain a relative impact on the path taken by the student. A BN is used to predict the probability of success, by taking historical data and student profiles into account. Usually, these profiles are defined beforehand; however, in our approach, some characteristics of these profiles, such as the level of knowledge, are classified automatically through supervised and/or unsupervised learning. By using ACO and BN, a fitness function, responsible for automatically selecting the next course in the learning graph, is defined. This is done by generating a path which maximizes the probability of each user??s success on the course. Therefore, the path can change in order to adapt itself to learners?? preferences and needs, by taking into account the pedagogical weight of each learning unit and the social behaviour of the system.     

Realistic real-time sound re-synthesis and processing for interactive virtual worlds

We present new GPU-based techniques for implementing linear digital filters for real-time audio processing. Our solution for recursive filters is the first presented in the literature. We demonstrate the relevance of these algorithms to computer graphics by synthesizing realistic sounds of colliding objects made of different materials, such as glass, plastic, and wood, in real time. The synthesized sounds can be parameterized by the object materials, velocities, and collision angles. Despite its flexibility, our approach uses very little memory, since it essentially requires a set of coefficients representing the impulse response of each material sound. Such features make our approach an attractive alternative to traditional CPU-based techniques that use playback of pre-recorded sounds.     

Invariant-driven specifications in Maude

This work presents a general mechanism for executing specifications that comply with given invariants, which may be expressed in different formalisms and logics. We exploit Maude’s reflective capabilities and its properties as a general semantic framework to provide a generic strategy that allows us to execute Maude specifications taking into account user-defined invariants. The strategy is parameterized by the invariants and by the logic in which such invariants are expressed. We experiment with different logics, providing examples for propositional logic, (finite future time) linear temporal logic and metric temporal logic.     

Microfluidic device with dual-channel fluorescence acquisition for quantification/identification of cancer cells

This paper presents an optofluidic device for cell discrimination with two independent interrogation regions. Pumping light is coupled to the device, and cell fluorescence is extracted from the two interrogation zones by using optical fibers embedded in the optofluidic chip. To test the reliability of this device, AU-565 cells—expressing EpCAM and HER2 receptors—and RAMOS cells were mixed in a controlled manner, confined inside a hydrodynamic focused flow in the microfluidic chip and detected individually so that they could be discriminated as positive (signal reception from fluorescently labeled antibodies from the AU-565 cells) or negative events (RAMOS cells). A correlation analysis of the two signals reduces the influence of noise on the overall data.