205 research outputs found
A service oriented architecture to provide data mining services for non-expert data miners
In today's competitive market, companies need to use discovery knowledge techniques to make better, more informed decisions. But these techniques are out of the reach of most users as the knowledge discovery process requires an incredible amount of expertise. Additionally, business intelligence vendors are moving their systems to the cloud in order to provide services which offer companies cost-savings, better performance and faster access to new applications. This work joins both facets. It describes a data mining service addressed to non-expert data miners which can be delivered as Software-as-a-Service. Its main advantage is that by simply indicating where the data file is, the service itself is able to perform all the process. © 2012 Elsevier B.V. All rights reserved
S3Mining: A model-driven engineering approach for supporting novice data miners in selecting suitable classifiers
Data mining has proven to be very useful in order to extract information from data in many different contexts. However, due to the complexity of data mining techniques, it is required the know-how of an expert in this field to select and use them. Actually, adequately applying data mining is out of the reach of novice users which have expertise in their area of work, but lack skills to employ these techniques. In this paper, we use both model-driven engineering and scientific workflow standards and tools in order to develop named S3Mining framework, which supports novice users in the process of selecting the data mining classification algorithm that better fits with their data and goal. To this aim, this selection process uses the past experiences of expert data miners with the application of classification techniques over their own datasets. The contributions of our S3Mining framework are as follows: (i) an approach to create a knowledge base which stores the past experiences of experts users, (ii) a process that provides the expert users with utilities for the construction of classifiers? recommenders based on the existing knowledge base, (iii) a system that allows novice data miners to use these recommenders for discovering the classifiers that better fit for solving their problem at hand, and (iv) a public implementation of the framework?s workflows. Finally, an experimental evaluation has been conducted to shown the feasibility of our framework
Coherent manipulation of three-qubit states in a molecular single-ion magnet
We study the quantum spin dynamics of nearly isotropic Gd3+ ions entrapped in polyoxometalate molecules and diluted in crystals of a diamagnetic Y3+ derivative. The full energy-level spectrum and the orientations of the magnetic anisotropy axes have been determined by means of continuous-wave electron paramagnetic resonance experiments, using X-band (9-10 GHz) cavities and on-chip superconducting waveguides and 1.5-GHz resonators. The results show that seven allowed transitions between the 2S+1 spin states can be separately addressed. Spin coherence T2 and spin-lattice relaxation T1 rates have been measured for each of these transitions in properly oriented single crystals. The results suggest that quantum spin coherence is limited by residual dipolar interactions with neighbor electronic spins. Coherent Rabi oscillations have been observed for all transitions. The Rabi frequencies increase with microwave power and agree quantitatively with predictions based on the spin Hamiltonian of the molecular spin. We argue that the spin states of each Gd3+ ion can be mapped onto the states of three addressable qubits (or, alternatively, of a d=8-level "qudit"), for which the seven allowed transitions form a universal set of operations. Within this scheme, one of the coherent oscillations observed experimentally provides an implementation of a controlled-controlled-NOT (or Toffoli) three-qubit gate
Fomentando el trabajo autónomo mediante técnicas de gamificación
A pesar de llevar ya unos años inmersos en el Espacio Europeo de Educación Superior, aún existe un número apreciable de alumnos que no sigue las asignaturas de manera continuada, sino que se limita a estudiar cuando hay pruebas de evaluación. Con objeto de fomentar el trabajo continuo y cambiar las rutinas de estudio, se gamificaron dos asignaturas de la materia de bases de datos bajo estrategias distintas: una, basada en clasificación y otra, en medallas. Estas experiencias se describen y analizan en detalle atendiendo a la valoración de los docentes y a la opinión de los alumnos recogida mediante una encuesta anónima. Las experiencias tuvieron lugar en el curso académico 2017-18 con una participación total de 78 alumnos. Como resultado, se señalan consideraciones que puedan orientar a otros docentes en la propuesta de iniciativas de gamificación.Despite the existence of the European Higher Education Area for quite some years already, a considerable number of students still do not follow subjects continuously during the course. Instead, they limit their work to the study of any graded items. We promoted continuous work with the aim of changing study rutines and of improving the learning outcome. This promotion was based on the gamification of two subjects of database curricula following two different gamification strategies: the first one was defined around a ranking, while the second one consisted in badges earning. These experiences are described and analyzed in this work, taking into account the assessment of the teachers and the students? opinion gathered through a survey. Analyzed data correspond to the 2017-18 edition of each course with a participation of 78 students. As a result, we point out some considerations that may be of interest for teachers when formulating gamification initiatives.Este trabajo ha sido desarrollado en el marco del Proyecto de Innovación Docente de la Universidad de Cantabria
Desarrollo Eficiente de Lenguajes Específicos de Dominio para la Ejecución de Procesos de Minería de Datos
Aunque las técnicas de minería de datos están consiguiendo cada día una mayor popularidad, su complejidad impide que sean aún utilizables por personas sin un sólido conocimiento en las mismas. Una posible solución, ya explorada por los autores de este artículo, es la construcción de Lenguajes Específicos de Dominio que proporcionen una serie de primitivas de alto nivel para la ejecución de procesos de minería de datos. Dichas primitivas sólo hacen referencia a terminología propia del dominio analizado, enmascarando detalles técnicos de bajo nivel. No obstante, la construcción de un lenguaje específico de dominio puede ser un proceso costoso. Este artículo muestra cómo reducir los tiempos de desarrollo de estos lenguajes de análisis mediante la reutilización de partes comunes de estos DSLs.Este trabajo ha sido parcialmente financiado por el Gobierno de Cantabria (España) mediante el Programa de Personal Investigador en Formación Predoctoral de la Universidad de Cantabria y por el Gobierno de España en el proyecto TIN2014-56158-C4-2-P(M2C2)
On the Automated Transformation of Domain Models into Tabular Datasets
We are surrounded by ubiquitous and interconnected soft- ware systems which gather valuable data. The analysis of these data, although highly relevant for decision making, cannot be performed di- rectly by business users, as its execution requires very speci c technical knowledge in areas such as statistics and data mining. One of the com- plexity problems faced when constructing an analysis of this kind resides in the fact that most data mining tools and techniques work exclusively over tabular-formatted data, preventing business users from analysing excerpts of a data bundle which have not been previously traduced into this format by an expert. In response, this work presents a set of transfor- mation patterns for automatically generating tabular data from domain models. The described patterns have been integrated into a language, which allows business users to specify the elements of a domain model that should be considered for data analysis.This work has been partially funded by the Government of Cantabria (Spain) under the doctoral studentship program from the University of Cantabria, and by the Spanish Government under grant TIN2014- 56158-C4-2-P (M2C2)
Un marco para democratizar la minería de datos: propuesta inicial y retos
Movimientos como el de datos abiertos posibilitan que cada vez haya una mayor disponibilidad de datos accesibles para su reutilización. A pesar de que el número de herramientas analíticas que están a nuestra disposición crece cada día, lamentablemente ninguna permite realizar un proceso de extracción de conocimiento directo a usuarios con poca o nula experiencia en el uso de la estadística y de algoritmos de minería de datos. En este artículo se presenta una aproximación a un marco KaaS (Knowledge as a Service) que posibilite a usuarios no expertos la extracción de conocimiento a partir de un conjunto de datos. Se muestra que la propuesta es viable y se plantean los retos aún abiertos
Observation of inhibited electron-ion coupling in strongly heated graphite
Creating non-equilibrium states of matter with highly unequal electron and lattice temperatures (Tele≠Tion) allows unsurpassed insight into the dynamic coupling between electrons and ions through time-resolved energy relaxation measurements. Recent studies on low-temperature laser-heated graphite suggest a complex energy exchange when compared to other materials. To avoid problems related to surface preparation, crystal quality and poor understanding of the energy deposition and transport mechanisms, we apply a different energy deposition mechanism, via laser-accelerated protons, to isochorically and non-radiatively heat macroscopic graphite samples up to temperatures close to the melting threshold. Using time-resolved x ray diffraction, we show clear evidence of a very small electron-ion energy transfer, yielding approximately three times longer relaxation times than previously reported. This is indicative of the existence of an energy transfer bottleneck in non-equilibrium warm dense matter
Can robotic-based top-down rehabilitation therapies improve motor control in children with cerebral palsy? A perspective on the CPWalker project
[EN] Cerebral Palsy (CP) is one of the most severe disabilities in childhood, and it demands important costs in health, education, and social services. CP is caused by damage to or abnormalities inside the developing brain that disrupt the brain's ability to control movement and maintain posture. Furthermore, CP is often associated with sensory deficits, cognition impairments, communication and motor disabilities, behavior issues, seizure disorder, pain, and secondary musculoskeletal problems. According to the literature, motor modules are peripheral measurements related to automatic motor control. There is a lack of evidence of change in motor modules in children with CP when different treatment approaches have been evaluated. Thus, new strategies are needed to improve motor control in this population.
Robotic-based therapies are emerging as an effective intervention for gait rehabilitation in motor disorders such as stroke, spinal cord injury, and CP. There is vast clinical evidence that neural plasticity is the central core of motor recovery and development, and on-going studies suggest that robot-mediated intensive therapy could be beneficial for improved functional recovery. However, current robotic strategies are focused on the peripheral neural system (PNS) facilitating the performance of repetitive movements (a bottom-up approach). Since CP affects primarily brain structures, both the PNS and the central nervous system (CNS) should to be integrated in a physical and cognitive rehabilitation therapy (a top-down approach).
This paper discusses perspectives of the top-down approach based on a novel robot-assisted rehabilitative system. Accordingly, the CPWalker robotic platform was developed to support novel therapies for CP rehabilitation. This robotic platform (Smart Walker + exoskeleton) is controlled by a multimodal interface enabling the interaction of CP infants with robot-based therapies. The aim of these therapies is to improve the physical skills of infants with CP using a top-down approach, in which motor related brain activity is used to drive robotic physical rehabilitation therapies. Our hypothesis is that the CPWalker concept will promote motor learning and this improvement will lead to significant improvements in automatic motor control.Lerma Lara, S.; Martínez Caballero, I.; Bayón, C.; Del Castillo, M.; Serrano, I.; Raya, R.; Belda Lois, JM.... (2016). Can robotic-based top-down rehabilitation therapies improve motor control in children with cerebral palsy? A perspective on the CPWalker project. Biomedical Research and Clinical Practice. 22-26. doi:10.15761/BRCP.1000106S222
Evolution of metabolic risk factors over a two-year period in a cohort of first episodes of psychosis
Patients with a first episode of psychosis (FEP) display a broad range of metabolic risk factors related to the development of diverse medical comorbidities. Initial stages of these disorders are essential in understanding the increased vulnerability of developing cardiometabolic disturbances, associated with a reduced life expectancy. This study aimed to evaluate the metabolic profile of a cohort of patients with a FEP and its evolution during a two year follow-up, as well as the factors that influence the changes in their metabolic status. 16 participating centers from the PEPs Project recruited 335 subjects with a FEP and 253 matched healthy controls, aged 9–35 years. We investigated a set of anthropometric measures, vital signs and laboratory data obtained from each participant over two years in a prospective, naturalistic study. From the beginning of the study the FEP group showed differences in the metabolic profile compared to the control group, together with a progressive worsening in the major part of the analyzed variables during the follow-up period, with higher rates of obesity and metabolic syndrome. Certain risk factors were related to determinate clinical variables such as male gender, the presence of affective symptoms or an early onset or to treatment variables such as the use of antipsychotic polypharmacy, antidepressants or mood stabilizers. Our results highlight the extremely high risk of patients at early phases of schizophrenia and other psychotic disorders of developing cardiovascular comorbidity and the fast worsening of the metabolic profile during the first two years
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