The crystal structure of murrayazoline (Mahanimbidine,curryangin)

Riassunto La struttura del murrayazoline, un'alcoloide carbazole, é stata confermata per via cristallografica con i raggi X.     

Production planning problem with pricing under random yield: CVaR criterion

In this paper, we address a basic production planning problem with price dependent demand and stochastic yield of production. We use price and target quantity as decision variables to lower the risk of low yield. The value of risk control becomes more important especially for products with short life cycle. This is because, the profit implications of low yield might be unbearable in the short run. We apply Conditional Value at Risk （CVaR） to model the, risk. CVaR measure is a coherent risk measure and thereby having nice conceptual and mathematical underpinnings. It is also widely used in practice. We consider the problem under general demand function and general distribution function of yield and find sufficient conditions under which the problem has a unique local maximum. We also both analytically and numerically analyze the impact of parameter change on the optimal solution. Among our results, we analytically show that with increasing risk aversion, the optimal price increases. This relation is opposite to that of in Newsvendor problem where the uncertainty lies in demand side.     

Application of SSM in tackling problematical situations from academicians’ viewpoints

In recent years, a wide variety of studies have applied soft systems methodology (SSM) to address the complexities of the messy situations. This paper seeks to identify 1) application areas and 2) application levels of the use of SSM in dealing with problematical situations. To do so, 149 articles published between 2000 and 2015 were studied. The findings revealed the application of SSM in new application areas such as sustainable development, knowledge management and project management. The results of this study also indicated that researchers applied SSM at three levels: SSM as a process of inquiry, SSM as an action-oriented methodology, and the hybrid use of SSM. Based on the findings, SSM at the level of a single methodology for bringing out changes has been less welcomed by researchers, but the application levels of inquiry processes and hybrid approaches have been more utilized. This suggests that in the correspondence of SSM with the nature or situation of problems, a sort of incommensurability is witnessed. Factors arising from the nature of the problem, inadequate mastery of the researcher over SSM or the limitations of SSM can exert an influence on this incommensurability.     

Intrusion Detection System Using Voting-Based Neural Network

Several security solutions have been proposed to detect network abnormal behavior. However, successful attacks is still a big concern in computer society. Lots of security breaches, like Distributed Denial of Service(DDoS),botnets, spam, phishing, and so on, are reported every day, while the number of attacks are still increasing. In this paper, a novel voting-based deep learning framework, called VNN, is proposed to take the advantage of any kinds of deep learning structures. Considering several models created by different aspects of data and various deep learning structures, VNN provides the ability to aggregate the best models in order to create more accurate and robust results. Therefore, VNN helps the security specialists to detect more complicated attacks. Experimental results over KDDCUP'99 and CTU-13, as two well known and more widely employed datasets in computer network area, revealed the voting procedure was highly effective to increase the system performance, where the false alarms were reduced up to 75% in comparison with the original deep learning models, including Deep Neural Network(DNN), Convolutional Neural Network(CNN), Long Short-Term Memory(LSTM), and Gated Recurrent Unit(GRU).     

Cu-Zn-Al2O3 nanocomposites: study of microstructure,corrosion, and wear properties

Alumina nanoparticles were added to a Cu-Zn alloy to investigate their effect on the microstructural, tribological, and corrosion properties of the prepared alloys. Alloying was performed using a mixture of copper and zinc powders with 0vol% and 5vol% of α-Al nanopowder in a satellite ball mill. The results showed that the Cu-Zn solid solution formed after 18 h of mechanical alloying. The mechan-ically alloyed powder was compacted followed by sintering of the obtained green compacts at 750℃ for 30 min. Alumina nanoparticles were uniformly distributed in the matrix of the Cu-Zn alloy. The tribological properties were evaluated by pin-on-disk wear tests, which revealed that, upon the addition of alumina nanoparticles, the coefficient of friction and the wear rate were reduced to 20% and 40%, respectively. The corrosion properties of the samples exposed to a 3.5wt% NaCl solution were studied using the immersion and potentiodynamic polarization methods, which revealed that the addition of alumina nanoparticles reduced the corrosion current of the nanocomposite by 90%.     

Bandwidth optimization of a Planar Inverted-F Antenna using binary and real coded genetic algorithms

With the exponential development of mobile communications and the miniaturization of radio frequency transceivers, the need for small and low profile antennas at mobile frequencies is constantly growing. Therefore, new antennas should be developed to provide larger bandwidth and at the same time small dimensions. Although the gain in bandwidth performances of an antenna are directly related to its dimensions in relation to the wavelength, the aim is to keep the overall size of the antenna constant and from there, find the geometry and structure that give the best performance. The design and bandwidth optimization of a Planar Inverted-F Antenna (PIFA) were introduced in order to achieve a larger bandwidth in the 2 GHz band, using two optimization techniques based upon genetic algorithms (GA), namely the Binary Coded GA (BCGA) and Real-Coded GA (RCGA). During the optimization process, the different PIFA models were evaluated using the finite-difference time domain (FDTD) method-a technique belonging to the general class of differential time domain numerical modeling methods.     

Fabrication and characterization of nanocrystalline Al/Al12（Fe,V）3Si alloys by consolidation of mechanically alloyed powders

The aim of this study was to produce bulk nanocrystalline Al/Al12（Fe,V）3Si alloys by mechanical alloying （MA） and subsequent hot pressing （HP） of elemental powders. A nanostructured Al-based solid solution was formed by MA of elemental powders for 60 h. After HP of the as-milled powders at 550℃ for 20 min, the Al12（Fe,V）3Si phase was precipitated in a nanocrystalline Al matrix. Scanning electron microscopy （SEM） images of the bulk samples represented a homogeneous and uniform microstructure that was superior to those previously obtained by rapid solidification-powder metallurgy （RS-PM）. Nanostructured Al-8.5Fe-1.3V-1.7Si and Al-11.6Fe-1.3V-2.3Si alloys ex-hibited high HV hardness values of～205 and～254, respectively, which are significantly higher than those reported for the RS-PM counter-parts.