Inometric methods and measures for sharing knowledge over internet

This paper deals with knowledge sharing over Internet. After defining the concept, we will discuss work aimed at creating a technical system to implement it and at measuring the quality of results obtained. However, the reader will quickly see that the text is organized to address the theme of this special issue of Scientometrics. Models, methods and measures characterize scientometric research. What problems arise in attempting to develop them for Internet? In order to answer this question, it is important to distinguish between two schools of practice in the scientometric research field: the first derives from applied statistics and is called bibliometrics; the second derives from cognitive sociology and is called infometrics (Turner, 1994).

     

Robust control of doubly fed induction generator for stand-alone applications

The doubly fed induction generator (DFIG) is generally used in the production of the electric energy and more specifically in wind turbines. Currently, a problem of electrical machine control and especially for wind turbines is the change of internal parameters of the machine, which greatly deteriorates the control. In addition, for stand-alone applications, the load and wind speed change frequently. In this paper, a robust control strategy based on the H_∞ control theory is developed for the independent control of the stator voltage amplitude and frequency of a stand-alone DFIG. The DFIG is fed through the rotor windings by a voltage inverter controlled by Space Vector Modulation (SVM). A capacitive and inductive filter is introduced to reduce harmonics on stator voltages and rotor currents. The robust control strategy rejects all the disturbances that may affect the system and that result from the variations of machine parameters, of the rotor speed and of the load. Experimental tests are carried out to verify the effectiveness of the robust control through a comparison with the classical PI regulator in the framework of the Field Oriented Control (FOC) strategy of the DFIG.     

A systematic literature review of machine learning applications in IoT

The Internet of Things (IoT) is a network of interconnected smart objects having capabilities that collectively form an ecosystem and enable the delivery of smart services to users. The IoT is providing several benefits into people's lives through the environment. The various applications that are run in the IoT environment offer facilities and services. The most crucial services provided by IoT applications are quick decision for efficient management. Recently, machine learning (ML) techniques have been successfully used to maximize the potential of IoT systems. This paper presents a systematic review of the literature on the integration of ML methods in the IoT. The challenges of IoT systems are split into two categories: fundamental operation and performance. We also look at how ML is assisting in the resolution of fundamental system operation challenges such as security, big data, clustering, routing, and data aggregation.     

Hairy root nodulation of Casuarina glauca: a system for the study of symbiotic gene expression in an actinorhizal tree

The purpose of this study was to establish a fast system for producing transgenic actinorhizal root nodules of Casuarina glauca. Agrobacterium rhizogenes strain A4RS carrying the p35S-gusA-int gene construct was used to induce hairy roots on hypocotyls of 3-week-old C. glauca seedlings. Three weeks after wounding, the original root system was excised, and composite plants consisting of transgenic roots on untransformed shoots were transferred to test tubes to be inoculated with Frankia. The actinorhizal nodules formed on transformed roots had the nitrogenase activity and morphology of untransformed nodules. beta-Glucuronidase (GUS) activity was examined in transgenic roots and nodules by fluorometric and histochemical assays. The results indicate that transgenic nodules generated with this root transformation system could facilitate the molecular study of symbiotic nitrogen fixation in actinorhizal trees.     

Photocatalytic reduction of Cr(VI) on the new hetero-system CuAl2O4/TiO2

A magnetic adsorbent, amine-functionalized silica magnetite (NH(2)/SiO(2)/Fe(3)O(4)), has been synthesized to behave as an anionic or cationic adsorbent by adjusting the pH value of the aqueous solution to make amino groups protonic or neutral. NH(2)/SiO(2)/Fe(3)O(4) were used to adsorb copper ions (metal cation) and Reactive Black 5 (RB5, anionic dye) in an aqueous solution in a batch system, and the maximum adsorption were found to occur at pH 5.5 and 3.0, respectively. The adsorption equilibrium data were all fitted the Langmuir isotherm equation reasonably well, with a maximum adsorption capacity of 10.41 mg g(-1) for copper ions and of 217 m g g(-1) for RB5. A pseudo-second-order model also could best describe the adsorption kinetics, and the derived activation energy for copper ions and RB5 were 26.92 kJ mol(-1) and 12.06 kJ mol(-1), respectively. The optimum conditions to desorb cationic and anionic adsorbates from NH(2)/SiO(2)/Fe(3)O(4) were provided by a solution with 0.1M HNO(3) for copper ions and with 0.05 M NaOH for RB5.     

TEM investigation of the tempering behaviour of the maraging PH 17.4 Mo stainless steel

The PH 17-4 Mo steel (Z6 CND 17.04.02), used in the steam generator of nuclear reactors, was investigated in order to determine the structural evolution occurring during tempering carried out under various conditions of duration and temperature. The formation and growth of different types of carbides such as Mo₂C, M₂₃C₆ and M₇C₃ and of Fe₂Mo intermetallic compound were studied and also of reversed austenite. A small secondary hardening peak was observed for tempering close to 400' C which is related to the Mo₂C carbide precipitation; beyond this temperature, softening occurs.     

From UML/SPT models to schedulability analysis: approach and a prototype implementation using ATL

Model Driven Architecture (MDA) is a software development approach promoted by the OMG. MDA is based on two key concepts, models and model transformations. Several kinds of models are generally used throughout the development process to specify a software system and to support its analysis and validation. UML and its extensions, such as the UML profile for real-time systems (UML/SPT), are commonly used to define the structure and the behavior of software systems while other models, such as performance models or schedulability models, are more suitable for performance or schedulability analysis, respectively. In this paper we discuss a model transformation enabling the derivation of schedulability analysis models from UML/SPT models. As a proof of concepts, we present a prototype implementation of this model transformation using ATL. We provide a definition of the source and target metamodels using the metamodel specification language KM3 and we specify the transformation in an ATL module. We discuss the merits and limitations of our approach and of its implementation.