Relational Learning with GPUs: Accelerating Rule Coverage

Relational learning algorithms mine complex databases for interesting patterns. Usually, the search space of patterns grows very quickly with the increase in data size, making it impractical to solve important problems. In this work we present the design of a relational learning system, that takes advantage of graphics processing units (GPUs) to perform the most time consuming function of the learner, rule coverage. To evaluate performance, we use four applications: a widely used relational learning benchmark for predicting carcinogenesis in rodents, an application in chemo-informatics, an application in opinion mining, and an application in mining health record data. We compare results using a single and multiple CPUs in a multicore host and using the GPU version. Results show that the GPU version of the learner is up to eight times faster than the best CPU version.     

Micromixing with spark-generated cavitation bubbles

The intrinsic laminarity of microfluidic devices impedes the mixing of multiple fluids over short temporal or spatial scales. Despite the existence of several mixers capable of stirring and stretching the flows to promote mixing, most approaches sacrifice temporal or spatial control, portability, or flexibility in terms of operating flow rates. Here, we report a novel method for rapid micromixing based on the generation of cavitation bubbles. By using a portable battery-powered electric circuit, we induce a localized electric spark between two tip electrodes perpendicular to the flow channel that results in several cavitation events. As a result, a vigorous stirring mechanism is induced. We investigate the spatiotemporal dynamics of the spark-generated cavitation bubbles and quantify the created flow disturbance. We demonstrate rapid (in the millisecond timescale) and efficient micromixing (up to 98%) within a length scale of only 200 µm and over a flow rate ranging from 5 to 40 µL/min.     

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.     

Semantic-based authorization architecture for Grid

There are a few issues that still need to be covered regarding security in the Grid area. One of them is authorization where there exist good solutions to define, manage and enforce authorization policies in Grid scenarios. However, these solutions usually do not provide Grid administrators with semantic-aware components closer to the particular Grid domain and easing different administration tasks such as conflict detection or resolution. This paper defines a proposal based on Semantic Web to define, manage and enforce security policies in a Grid scenario. These policies are defined by means of semantic-aware rules which help the administrator to create higher-level definitions with more expressiveness. These rules also permit performing added-value tasks such as conflict detection and resolution, which can be of interest in medium and large scale scenarios where different administrators define the authorization rules that should be followed before accessing a resource in the Grid. The proposed solution has been also tested providing some reasonable response times in the authorization decision process.     

Proof Pearl: a Formal Proof of Higman��s Lemma in ACL2

Higman??s lemma is an important result in infinitary combinatorics, which has been formalized in several theorem provers. In this paper we present a formalization and proof of Higman??s Lemma in the ACL2 theorem prover. Our formalization is based on a proof by Murthy and Russell, where the key termination argument is justified by the multiset relation induced by a well-founded relation. To our knowledge, this is the first mechanization of this proof.     

Applying intelligent agents and semantic web services in eGovernment environments

The increasing volume of eGovernment‐related services is demanding new approaches for service integration and interoperability in this domain. Semantic web (SW) technologies and applications can leverage the potential of eGovernment service integration and discovery, thus tackling the problems of semantic heterogeneity characterizing eGovernment information sources and the different levels of interoperability. eGovernment services will therefore be semantically described in the foreseeable future. In an environment with semantically annotated services, software agents are essential as the entities responsible for exploiting the semantic content in order to automate some tasks, and so enhance the user's experience. In this paper, we present a framework that provides a seamless integration of semantic web services and intelligent agents technologies by making use of ontologies to facilitate their interoperation. The proposed framework can assist in the development of powerful and flexible distributed systems in complex, dynamic, heterogeneous, unpredictable and open environments. Our approach is backed up by a proof‐of‐concept implementation, where the breakthrough of integrating disparate eGovernment services has been tested.     

An Analysis of Edge Detection by Using the Jensen-Shannon Divergence

This work constitutes a theoretical study of the edge-detection method by means of the Jensen-Shannon divergence, as proposed by the authors. The overall aim is to establish formally the suitability of the procedure of edge detection in digital images, as a step prior to segmentation. In specific, an analysis is made not only of the properties of the divergence used, but also of the method's sensitivity to the spatial variation, as well as the detection-error risk associated with the operating conditions due to the randomness of the spatial configuration of the pixels. Although the paper deals with the procedure based on the Jensen-Shannon divergence, some problems are also related to other methods based on local detection with a sliding window, and part of the study is focused to noisy and textured images.     

Guidelines for the incremental identification of aspects in requirements specifications

The desired principle of separation of concerns in software development can be jeopardized by the so-called crosscutting concerns, which tend to be scattered over (and tangled with) the functionality of the modular units of a system. The correct identification of such concerns (and their encapsulation into separate artifacts) is thereby considered a way to improve software understanding and evolution. Pursuing a proper management of concerns from the requirements engineering stage can greatly benefit the entire software life-cycle. In this paper, we propose conceptual guidelines on how to perform the identification of crosscutting concerns in the process of building requirements specifications. We argue that the identification must be carried out in an incremental way, to encapsulate apart the crosscutting concerns even if they have not emerged completely yet.

Group weighted finite transducers

We consider weighted finite transducers over arbitrary groups, that is finite transducers having a counter in which, at any step, a value of the group is stored but no information regarding the content of this counter is available until the computation is finished. The computation is valid if the counter value is the neutral element of the group. We generalize here some results from [8] and [17]. Received: 28 January 2001 / 5 June 2001     

A socioeconomic model for managing water resources in Alicante,southeast Spain

The study analyzes variables that influence the water management model based on a simultaneous relationship between competing demands in the Marina Baja of Alicante, using a methodology that directly links together urban and irrigation demands, making them relevant to each other from a socioeconomic point of view. The paper identifies the relevant variables of this model and the agent behaviour in a closed and joint system. It also aims to demonstrate that by considering water demands for different yet simultaneous uses and regarding clean and reclaimed waters as integrated resources, the system could remain in equilibrium without external water supplies.