The main purpose of a gene interaction network is to map the relationships of the genes that are out of sight when a genomic study is tackled. DNA microarrays allow the measure of gene expression of thousands of genes at the same time. These data constitute the numeric seed for the induction of the gene networks. In this paper, we propose a new approach to build gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling. The interactions induced by the Bayesian classifiers are based both on the expression levels and on the phenotype information of the supervised variable. Feature selection and bootstrap resampling add reliability and robustness to the overall process removing the false positive findings. The consensus among all the induced models produces a hierarchy of dependences and, thus, of variables. Biologists can define the depth level of the model hierarchy so the set of interactions and genes involved can vary from a sparse to a dense set. Experimental results show how these networks perform well on classification tasks. The biological validation matches previous biological findings and opens new hypothesis for future studies. 相似文献
Bankruptcy prediction has long time been an active research field in finance. One of the main approaches to this issue is
dealing with it as a classification problem. Among the range of instruments available, we focus our attention on the Evolutionary
Nearest Neighbor Classifier (ENPC). In this work we assess the performance of the ENPC comparing it to six alternatives. The
results suggest that this algorithm might be considered a good choice. 相似文献
Haptic devices allow a user to feel either reaction forces from virtual interactions or reaction forces reflected from a remote
site during a bilateral teleoperation task. Also, guiding forces can be exerted to train the user in the performance of a
virtual task or to assist him/her to safely teleoperate a robot. The generation of guiding forces relies on the existence
of a motion plan that provides the direction to be followed to reach the goal from any free configuration of the configuration
space (-space). This paper proposes a method to obtain such a plan that interleaves a sampling-based exploration of -space with an efficient computation of harmonic functions. A deterministic sampling sequence (with a bias based on harmonic
function values) is used to obtain a hierarchical cell decomposition model of -space. A harmonic function is iteratively computed over the partially known model using a novel approach. The harmonic function
is the navigation function used as motion plan. The approach has been implemented in a planner (called the Kautham planner) that, given an initial and a goal configuration, provides: (a) a channel of cells connecting the cell that contains
the initial configuration with the cell that contains the goal configuration; (b) two harmonic functions over the whole -space, one that guides motions towards the channel and another that guides motions within the channel towards the goal; and
(c) a path computed over a roadmap built with the free samples of the channel. The harmonic functions and the solution path
are then used to generate the guiding forces for the haptic device. The planning approach is illustrated with examples on
2D and 3D workspaces.
This work was partially supported by the CICYT projects DPI2005-00112 and DPI2007-63665. 相似文献
Geographic Routing(GR)algorithms require nodes to periodically transmit HELLO messages to allow neigh- bors to know their positions(beaconing mechanism).Beacon-less routing algorithms have recently been proposed to reduce the control overheads due to these messages.However,existing beacon-less algorithms have not considered realistic physical layers.Therefore,those algorithms cannot work properly in realistic scenarios.In this paper we present a new beacon- less routing protocol called BOSS.Its design is based on the conclusions of our open-field experiments using Tmote-sky sensors.BOSS is adapted to error-prone networks and incorporates a new mechanism to reduce collisions and duplicate messages produced during the selection of the next forwarder node.We compare BOSS with Beacon-Less Routing(BLR) and Contention-Based Forwarding(CBF)algorithms through extensive simulations.The results show that our scheme is able to achieve almost perfect packet delivery ratio(like BLR)while having a low bandwidth consumption(even lower than CBF).Additionally,we carried out an empirical evaluation in a real testbed that shows the correctness of our simulation results. 相似文献
Typical request processing systems, such as web servers and database servers, try to accommodate all requests as fast as possible,
which can be described as a Best-Effort approach. However, different application items may have different quality-of-service
(QoS) requirements, and this can be viewed as an orthogonal concern to the basic system functionality. In this paper we propose
the QoS-Broker, a middleware for delivering QoS over servers and applications. We show its architecture to support contracts
over varied targets including queries, transactions, services or sessions, also allowing expressions on variables to be specified
in those targets. We also discuss how the QoS-Broker implements basic strategies for QoS over workloads. Our experimental
results illustrate the middleware by applying priority and weighted- fair-queuing based differentiation over clients and over
transactions, and also admission control, using a benchmark as a case-study. 相似文献
Stepwise multiple linear regression (SMLR) and principal components regression (PCR) have been used to predict the percentages of cows', goats' and ewes' milk in Iberico cheese, using the results obtained by electrophoretic analysis (PAGE and IEF) of whey proteins, using standard cheeses. Similar predictions of the percentages of milks from the three species were obtained when either SMLR or PCR were applied to the electrophoretic data, i.e. the optical intensity of the electrophoretic bands (PAGE or IEF) of the whey proteins. The root mean square error of prediction in cross-validation (RMSEPCV) was lower than 4% in all cases. 相似文献
Magnetic Resonance Materials in Physics, Biology and Medicine - Histogram-based metrics extracted from diffusion-tensor imaging (DTI) have been suggested as potential biomarkers for cerebral small... 相似文献
Cloud computing is becoming a very popular form of distributed computing, in which digital resources are shared via the Internet. The user is provided with an overview of many available resources. Cloud providers want to get the most out of their resources, and users are inclined to pay less for better performance. Task scheduling is one of the most important aspects of cloud computing. In order to achieve high performance from cloud computing systems, tasks need to be scheduled for processing by appropriate computing resources. The large search space of this issue makes it an NP-hard problem, and more random search methods are required to solve this problem. Multiple solutions have been proposed with several algorithms to solve this problem until now. This paper presents a hybrid algorithm called GSAGA to solve the Task Scheduling Problem (TSP) in cloud computing. Although it has a high ability to search the problem space, the Genetic Algorithm (GA) performs poorly in terms of stability and local search. It is therefore possible to create a stable algorithm by combining the general search capacities of the GA with the Gravitational Search Algorithm (GSA). Our experimental results indicate that the proposed algorithm can solve the problem with higher efficiency compared with the state-of-the-art.
Software Quality Journal - The number of electronic control units (ECU) installed in vehicles is increasingly high. Manufacturers must improve the software quality and reduce cost by proposing... 相似文献