Hybrid incremental modeling based on least squares and fuzzy K-NN for monitoring tool wear in turning processes

There is now an emerging need for an efficient modeling strategy to develop a new generation of monitoring systems. One method of approaching the modeling of complex processes is to obtain a global model. It should be able to capture the basic or general behavior of the system, by means of a linear or quadratic regression, and then superimpose a local model on it that can capture the localized nonlinearities of the system. In this paper, a novel method based on a hybrid incremental modeling approach is designed and applied for tool wear detection in turning processes. It involves a two-step iterative process that combines a global model with a local model to take advantage of their underlying, complementary capacities. Thus, the first step constructs a global model using a least squares regression. A local model using the fuzzy k-nearest-neighbors smoothing algorithm is obtained in the second step. A comparative study then demonstrates that the hybrid incremental model provides better error-based performance indices for detecting tool wear than a transductive neurofuzzy model and an inductive neurofuzzy model.

A fuzzy MCDA framework for safety assessment in the remediation of a uranium mill tailings site in Ukraine

The Pridneprovsky Chemical Plant was one of the largest uranium processing enterprises in the former USSR, producing a huge amount of uranium residues. The Zapadnoe tailings site contains most of these residues. We propose a theoretical framework based on multicriteria decision analysis and fuzzy logic to analyze different remediation alternatives for the Zapadnoe tailings, which simultaneously accounts for potentially conflicting economic, social and environmental objectives. We build an objective hierarchy that includes all the relevant aspects. Fuzzy rather than precise values are proposed for use to evaluate remediation alternatives against the different criteria and to quantify preferences, such as the weights representing the relative importance of criteria identified in the objective hierarchy. Finally, we suggest that remediation alternatives should be evaluated by means of a fuzzy additive multi-attribute utility function and ranked on the basis of the respective trapezoidal fuzzy number representing their overall utility.

An interactive method of fuzzy probability elicitation in risk analysis

Expert knowledge is used to assign probabilities to events in many risk analysis models. However, experts sometimes find it hard to provide specific values for these probabilities, preferring to express vague or imprecise terms that are mapped using a previously defined fuzzy number scale. The rigidity of these scales generates bias in the probability elicitation process and does not allow experts to adequately express their probabilistic judgments. We present an interactive method for extracting a fuzzy number from experts that represents their probabilistic judgments for a given event, along with a quality measure of the probabilistic judgments, useful in a final information filtering and analysis sensitivity process.

Fuzzy MCDA for remediation of a uranium tailing

The Pridneprovsky Chemical Plant was a largest uranium processing enterprises, producing a huge amount of uranium residues. The Zapadnoe tailings site contains the majority of these residues. We propose a theoretical framework based on Multi-Criteria Decision Analysis and fuzzy logic to analyse different remediation alternatives for the Zapadnoe tailings, in which potentially conflicting economic, radiological, social and environmental objectives are simultaneously taken into account. An objective hierarchy is built that includes all the relevant aspects. Fuzzy rather than precise values are proposed for use to evaluate remediation alternatives against the different criteria and to quantify preferences, such as the weights representing the relative importance of criteria identified in the objective hierarchy. Finally, it is proposed that remediation alternatives should be evaluated by means of a fuzzy additive multi-attribute utility function and ranked on the basis of the respective trapezoidal fuzzy number representing their overall utility.

Autonomous classification models in ubiquitous environments

Stream-mining approach is defined as a set of cutting-edge techniques designed to process streams of data in real time, in order to extract knowledge. In the particular case of classification, stream-mining has to adapt its behaviour to the volatile underlying data distributions, what has been called concept drift. Moreover, it is important to note that concept drift may lead to situations where predictive models become invalid and have therefore to be updated to represent the actual concepts that data poses. In this context, there is a specific type of concept drift, known as recurrent concept drift, where the concepts represented by data have already appeared in the past. In those cases the learning process could be saved or at least minimized by applying a previously trained model. This could be extremely useful in ubiquitous environments that are characterized by the existence of resource constrained devices. To deal with the aforementioned scenario, meta-models can be used in the process of enhancing the drift detection mechanisms used by data stream algorithms, by representing and predicting when the change will occur. There are some real-world situations where a concept reappears, as in the case of intrusion detection systems (IDS), where the same incidents or an adaptation of them usually reappear over time. In these environments the early prediction of drift by means of a better knowledge of past models can help to anticipate to the change, thus improving efficiency of the model regarding the training instances needed. By means of using meta-models as a recurrent drift detection mechanism, the ability to share concepts representations among different data mining processes is open. That kind of exchanges could improve the accuracy of the resultant local model as such model may benefit from patterns similar to the local concept that were observed in other scenarios, but not yet locally. This would also improve the efficiency of training instances used during the classification process, as long as the exchange of models would aid in the application of already trained recurrent models, that have been previously seen by any of the collaborative devices. Which it is to say that the scope of recurrence detection and representation is broaden. In fact the detection, representation and exchange of concept drift patterns would be extremely useful for the law enforcement activities fighting against cyber crime. Being the information exchange one of the main pillars of cooperation, national units would benefit from the experience and knowledge gained by third parties. Moreover, in the specific scope of critical infrastructures protection it is crucial to count with information exchange mechanisms, both from a strategical and technical scope. The exchange of concept drift detection schemes in cyber security environments would aid in the process of preventing, detecting and effectively responding to threads in cyber space. Furthermore, as a complement of meta-models, a mechanism to assess the similarity between classification models is also needed when dealing with recurrent concepts. In this context, when reusing a previously trained model a rough comparison between concepts is usually made, applying boolean logic. The introduction of fuzzy logic comparisons between models could lead to a better efficient reuse of previously seen concepts, by applying not just equal models, but also similar ones. This work faces the aforementioned open issues by means of: the MMPRec system, that integrates a meta-model mechanism and a fuzzy similarity function; a collaborative environment to share meta-models between different devices; a recurrent drift generator that allows to test the usefulness of recurrent drift systems, as it is the case of MMPRec. Moreover, this thesis presents an experimental validation of the proposed contributions using synthetic and real datasets.

Distal enhancer regulation by promoter derepression in topologically constrained DNA in vitro

Long-range promoter–enhancer interactions are a crucial regulatory feature of many eukaryotic genes yet little is known about the mechanisms involved. Using cloned chicken βA-globin genes, either individually or within the natural chromosomal locus, enhancer-dependent transcription is achieved in vitro at a distance of 2 kb with developmentally staged erythroid extracts. This occurs by promoter derepression and is critically dependent upon DNA topology. In the presence of the enhancer, genes must exist in a supercoiled conformation to be actively transcribed, whereas relaxed or linear templates are inactive. Distal protein–protein interactions in vitro may be favored on supercoiled DNA because of topological constraints. In this system, enhancers act primarily to increase the probability of rapid and efficient transcription complex formation and initiation. Repressor and activator proteins binding within the promoter, including erythroid-specific GATA-1, mediate this process.

The challenge of paleoecological stasis: reassessing sources of evolutionary stability.

The paleontological record of the lower and middle Paleozoic Appalachian foreland basin demonstrates an unprecedented level of ecological and morphological stability on geological time scales. Some 70-80% of fossil morphospecies within assemblages persist in similar relative abundances in coordinated packages lasting as long as 7 million years despite evidence for environmental change and biotic disturbances. These intervals of stability are separated by much shorter periods of ecological and evolutionary change. This pattern appears widespread in the fossil record. Existing concepts of the evolutionary process are unable to explain this uniquely paleontological observation of faunawide coordinated stasis. A principle of evolutionary stability that arises from the ecosystem is explored here. We propose that hierarchical ecosystem theory, when extended to geological time scales, can explain long-term paleoecological stability as the result of ecosystem organization in response to high-frequency disturbance. The accompanying stability of fossil morphologies results from "ecological locking," in which selection is seen as a high-rate response of populations that is hierarchically constrained by lower-rate ecological processes. When disturbance exceeds the capacity of the system, ecological crashes remove these higher-level constraints, and evolution is free to proceed at high rates of directional selection during the organization of a new stable ecological hierarchy.

A Meta-Analytic Review of Mindfulness-Based Interventions on Symptom Reduction: A Critique and Guide for Future Investigation.

Over the past decade, mindfulness practices have been used with increasing frequency as therapeutic components within cognitive behavioral treatment regimens. As is standard practice, prescriptive uses of mindfulness intervention are incorporated to improve end-state functioning by ameliorating problematic symptoms and conditions. Common change-targets include the control of cognitive and emotional content for purposes of enhancing psychological self-regulation and physical well-being. The term mindfulness applies to a heterogeneous range of practices, methods, and techniques. While there is no singular agreed upon definition for mindfulness, as a process concept, the term connotes an immediate, non-thetic access to events, wherein each occasioning event is experienced in toto within the broader contextual event-field, and distinct from intervening conceptual themes being noticed. Training in mindfulness practices may be conducted using individual, group, or small class formats. The current paper provides a meta-analytic review of 44 treatment outcome studies (extracted 1982 through 2006), which examines the clinical utility of mindfulness as the primary therapeutic approach. Results indicated that average effect sizes for mindfulness based interventions fell within the medium range for construct category variables examined (d = .56). These findings suggest that mindfulness training is a cost-effective treatment for a wide array of contemporary psychological problems and diagnoses, in addition to fostering positive psychology attributes such as quality and satisfaction with life. A critique of the research and recommendations for future research, including a need to examine the role of mindfulness as a tool for cultivating increased psychological acceptance and life satisfaction, is presented.

Análisis de susceptibilidad a los movimientos de ladera en los municipios de Tipuani, Guanay y Teoponte, (Bolivia).

Los deslizamientos de ladera son un problema importante en la región de los valles interandinos de Bolivia. Este estudio analiza la susceptibilidad o predisposición al movimiento de ladera de los municipios de Guanay, Teoponte y Tipuani, situados en el departamento de La Paz, Bolivia. La metodología aplicada es la Analityc Hierarchy/Network Process, o método AHP. Tras su aplicación en un Sistema de Información Geográfica, este método, devuelve valores de susceptibilidad bastante fiables. Las conclusiones que se extraen de este análisis ponen de relieve la necesidad de realizar estudios de detalle en algunas zonas de los tres municipios al haber lugares con una Muy Alta y Alta susceptibilidad al movimiento de ladera, que, además, interfieren con zonas pobladas y con caminos y carreteras principales que son importantes para la articulación social de la región.

An analysis of ASAP impact on the judicial system. SD:ASAP analytic study no. 4 - 1976. Final report.

National Highway Traffic Safety Administration, Office of Driver and Pedestrian Programs, Washington, D.C.

Oklahoma City ASAP - effectiveness and efficiency. Analytic study no. 1. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

An analysis of the impact of ASAP on the traffic safety system. Fourth analytic study.

National Highway Traffic Safety Administration, Washington, D.C.

An analysis of the impact of ASAP on the traffic safety system of Fairfax, Virginia - analytic study 4, court procedures: 1976. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

An analysis of the impact of ASAP on the traffic safety system in Columbus, Georgia from January, 1972 - December, 1974. Analytic study 4.

National Highway Traffic Safety Administration, Washington, D.C.

San Antonio Alcohol Safety Action Project - analytic study no. 4: final analysis of the judicial system 1972 through 1974.

National Highway Traffic Safety Administration, Washington, D.C.