Experiences in building a Grid-based platform to serve Earth observation training activities

Earth observation data processing and storing can be done nowadays only using distributed systems. Experiments dealing with a large amount of data are possible within the timeframe of a lesson and can give trainees the freedom to innovate. Following these trends and ideas, we have built a proof-of-the-concept platform, named GiSHEO, for Earth observation educational tasks. It uses Grid computing technologies to analyze and store remote sensing data, and combines them with eLearning facilities. This paper provides an overview of the GiSHEO's platform architecture and of its technical and innovative solutions.     

Using enzymatic numerical P systems for modeling mobile robot controllers

P systems (PSs) are powerful computing models based on the structure of a biological cell and on the way chemicals interact in complex biochemical reactions which take place in various compartments (or membranes) of the cell. A lot of interest has been focused on developing various forms of PSs, from cell-like to tissue-like structures. Most of the research effort has been concentrated on symbolical PSs. Numerical P systems (NPSs) have been introduced in 2006 for possible applications in economics and business processes but no other structures and applications concerning this type of PSs have been provided since then. This paper proposes a new class of NPSs, in which enzyme-like variables allow the existence of more than one production function in each membrane, while keeping the deterministic nature of the system. The way this new type of deterministic NPSs works and a possible use of it for modeling mobile robot controllers are detailed.     

Internal preference mapping and the issue of satiety

Internal preference mapping (IPM) and Landscape Segmentation Analysis® (LSA) are two techniques broadly used to unfold consumers’ overall product liking ratings and create spatial maps that will provide further insights on consumers’ preferences. IPM is based on a vector model while LSA involves an ideal point model. Through a simulation and the analysis of 27 market research data sets, it is shown that IPM consistently creates a hedonic dimension that prevents the identification of satiety prone attributes (intensities higher or lower than a optimal level being disliked by the consumers) on that dimension. As a result, subsequent steps taken upon generating an IPM map such as the investigation of drivers of liking, population segmentation and the estimation of optimal product profiles have also a strong likelihood of resulting in distorted results, the level of distortion being dependent on the actual configuration of the underlying structure that IPM tried to uncover. It is also shown that a technique based on ideal points such as LSA does not exhibit this systematic artifact when unfolding liking data. Consequently, sensory scientists and market researchers should use caution when interpreting and using results issued from an internal preference mapping analysis.     

Learning and clustering of fuzzy cognitive maps for travel behaviour analysis

In modern society, more and more attention is given to the increase in public transportation or bike use. In this regard, one of the most important issues is to find and analyse the factors influencing car dependency and the attitudes of people in terms of preferred transport mode. Although the individuals’ transport behavioural modelling is a complex task, it has a notable social and economic impact. Thus, in this paper, fuzzy cognitive maps are explored to represent the behaviour and operation of such complex systems. This soft-computing technique allows modelling how the travellers make decisions based on their knowledge of different transport modes properties at different levels of abstraction. These levels correspond to the hierarchy perception including different scenarios of travelling, different benefits of choosing a specific travel mode, and different situations and attributes related to those benefits. We use learning and clustering of fuzzy cognitive maps to describe travellers’ behaviour and change trends in different abstraction levels. Cluster estimations are done before and after the learning of the maps, in order to compare people’s way of thinking if only considering an initial view of a transport mode decision for a daily activity, and when they really have a deeper reasoning process in view of benefits and consequences. The results of this study will help transportation policy decision makers in better understanding of people’s needs and consequently will help them actualizing different policy formulations and implementations.     

The modification effect of different compounds for protection of magnesium against corrosion

A protective layers were prepared on a magnesium electrode by treatment in different solutions and times after modification in 0.15 M HCl for 20 seconds. The corrosion of magnesium coated protective layer with different compounds was studied by using potential-time, current-potential curves and AC impedance spectra. The coatings morphology depends on the treating bath compositions and immersion times. The protective efficiencies of the surface layers were calculated by using corrosion rates obtained by extrapolation of Tafel zones of current-potential curves to the corrosion potential and by using Stern-Geary equation with polarization resistance from impedance spectra.     

Series resistance determination of Au/Polypyrrole/p-Si/Al structure by current–voltage measurements at low temperatures

The current–voltage (I–V) characteristics of Polypyrrole(PPy)/p-Si/Al structure have been investigated as a function of temperature. A modified Norde function combined with conventional forward I–V method has been used to extract the junction parameters including the ideality factor, barrier height and series resistance. Norde function has been compared with the Cheung functions and it has been seen that there is a good agreement with both method for the barrier height values. However, the values of series resistance have very different especially towards to the lower temperatures. This is attributed to non-ideal I–V characteristics of the Au/PPy/p-Si/Al structure and non-pure Thermionic emission theory due to the low temperature effects.     

Visualization of trends using RadViz

Data mining is sometimes treating data consisting of items representing measurements of a single property taken in different time points. In this case data can be understood as a time series of one feature. It is no exception when the clue for evaluation of such data is related to their development trends as observed in several successive time points. From the qualitative point of view one can distinguish three basic types of behaviour between two neighbouring time points: the value of the feature is stable (remains the same), it grows or it falls. This paper is concerned with identification of typical qualitative development patterns as they appear in the windows of given length in the considered time-stamped data and their utilization for specification of interesting subgroups.     

基于ViBe的改进运动目标检测方法

提出一种基于ViBe算法的改进运动目标检测方法。改进的方法利用二十帧图像进行背景模型的初始化,通过比较SILTP特征值来对前后景像素进行分类,模型更新机制采用替代异常值的方式。在不同场景下的实验结果表明,改进后的算法对光照变化、鬼影产生和噪声具有强鲁棒性。     

Photocrosslinked biobased phase change material for thermal energy storage

A series of novel photocrosslinked biobased shape‐stabilized phase change materials (PCMs) based on octadecanol, eicosanol and docosanol have been prepared by UV technique for the purpose of thermal energy storage applications. Epoxidized soybean oil was reacted with acrylic acid to form acrylated soybean oil (ASO). The structure and composition, cross‐section morphology, thermal stability performances and phase change behaviors of ASO and UV‐cured PCMs were examined by using Attenuated total reflection fourier transform infrared spectroscopy, thermogravimetric analysis system (TGA), scanning electron microscopy, and differential scanning calorimetry. The results indicate that the UV‐cured biobased PCMs possess perfect phase change properties and a suitable working temperature range. The heating process phase change enthalpy is measured between 30 and 68 J/g, and the freezing process phase change enthalpy is found between 18 and 70 J/g. The decomposition of UV‐cured PCMs started at 260 °C and reached a maximum of 430 °C. All the biobased UV‐cured PCMs improved latent heat storage capacity in comparison with the pristine ASO sample. With the obtained results we conclude that, these materials promise a great potential in thermal energy storage applications. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43757.