Observer Based Control of a Class of Nonlinear Fractional Order Systems using LMI

Design of an observer based controller for a class of fractional order systems has been done. Fractional order mathematics is used to express the system and the proposed observer. Fractional order Lyapunov theorem is used to derive the closed-loop asymptotic stability. The gains of the observer and observer based controller are derived systematically using the linear matrix inequality approach. Finally, the simulation results demonstrate validity and effectiveness of the proposed observer based controller.

Comparison of The Fertilizer Properties of Ash Fractions from Medium-Sized (32 MW) and Small-Sized (6 MW) Municipal District Heating Plants

Due to the low heavy metal concentrations, the bottom ash from a 32 MW municipal district heating plant was determined to be a potential forest fertilizer as such. However, additional Ca would be needed, because its Ca concentration of 1.9- % (d.w.) was lower than the statutory Finnish minimum limit value of 6.0-% (d.w.) for Ca in forest fertilizer. Due to the elevated As concentration (53.0 mg/kg; d.w.) in the fly ash from the 32 MW municipal district heating plant, and Cr concentration (620 mg/kg; d.w.) in the ash fraction (i.e. mixture of the bottom ash and fly ash) from the 6 MW municipal district heating plant, which exceed the limit values of 30 mg/kg (d.w.) and 300 mg/kg (d.w.) for As and Cr, respectively, these residues are not suitable as forest fertilizers. Although these ash fractions cannot be used as a forest fertilizer as such, they can be used for the landscaping of landfills or in industrial and other areas that are closed to the public. However, an environmental permit is then needed.

How to Connect User Research and not so Forthcoming Technology Scenarios – The Extended Home Environment Case Study

This paper draws a methodological framework adopted within an internal Telecomitalia project aimed to identify, on a user centred base, the potential interest towards a technological scenario aimed to extend on a personal bubble the typical communication and media fruition home environment. The problem is that involving user in the early stage of the development of such disruptive technology scenario asking users opinions on something that users actually do not manage even in a rough manner could lead to wrong or distorted results. For that reason we chose an approach that indirectly aim to understand users hidden needs in order to obtain a meaningful picture of the possible interest for a technological proposition non yet easily understandable.

Predicting the Three Major Dimensions of the Learner-s Emotions from Brainwaves

This paper investigates how the use of machine learning techniques can significantly predict the three major dimensions of learner-s emotions (pleasure, arousal and dominance) from brainwaves. This study has adopted an experimentation in which participants were exposed to a set of pictures from the International Affective Picture System (IAPS) while their electrical brain activity was recorded with an electroencephalogram (EEG). The pictures were already rated in a previous study via the affective rating system Self-Assessment Manikin (SAM) to assess the three dimensions of pleasure, arousal, and dominance. For each picture, we took the mean of these values for all subjects used in this previous study and associated them to the recorded brainwaves of the participants in our study. Correlation and regression analyses confirmed the hypothesis that brainwave measures could significantly predict emotional dimensions. This can be very useful in the case of impassive, taciturn or disabled learners. Standard classification techniques were used to assess the reliability of the automatic detection of learners- three major dimensions from the brainwaves. We discuss the results and the pertinence of such a method to assess learner-s emotions and integrate it into a brainwavesensing Intelligent Tutoring System.

Development of a Neural Network based Algorithm for Multi-Scale Roughness Parameters and Soil Moisture Retrieval

The overall objective of this paper is to retrieve soil surfaces parameters namely, roughness and soil moisture related to the dielectric constant by inverting the radar backscattered signal from natural soil surfaces. Because the classical description of roughness using statistical parameters like the correlation length doesn't lead to satisfactory results to predict radar backscattering, we used a multi-scale roughness description using the wavelet transform and the Mallat algorithm. In this description, the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each having a spatial scale. A second step in this study consisted in adapting a direct model simulating radar backscattering namely the small perturbation model to this multi-scale surface description. We investigated the impact of this description on radar backscattering through a sensitivity analysis of backscattering coefficient to the multi-scale roughness parameters. To perform the inversion of the small perturbation multi-scale scattering model (MLS SPM) we used a multi-layer neural network architecture trained by backpropagation learning rule. The inversion leads to satisfactory results with a relative uncertainty of 8%.

The Long Run Relationship between Exports and Imports in South Africa: Evidence from Cointegration Analysis

This study empirically examines the long run equilibrium relationship between South Africa’s exports and imports using quarterly data from 1985 to 2012. The theoretical framework used for the study is based on Johansen’s Maximum Likelihood cointegration technique which tests for both the existence and number of cointegration vectors that exists. The study finds that both the series are integrated of order one and are cointegrated. A statistically significant cointegrating relationship is found to exist between exports and imports. The study models this unique linear and lagged relationship using a Vector Error Correction Model (VECM). The findings of the study confirm the existence of a long run equilibrium relationship between exports and imports.

Applying Fuzzy FP-Growth to Mine Fuzzy Association Rules

In data mining, the association rules are used to find for the associations between the different items of the transactions database. As the data collected and stored, rules of value can be found through association rules, which can be applied to help managers execute marketing strategies and establish sound market frameworks. This paper aims to use Fuzzy Frequent Pattern growth (FFP-growth) to derive from fuzzy association rules. At first, we apply fuzzy partition methods and decide a membership function of quantitative value for each transaction item. Next, we implement FFP-growth to deal with the process of data mining. In addition, in order to understand the impact of Apriori algorithm and FFP-growth algorithm on the execution time and the number of generated association rules, the experiment will be performed by using different sizes of databases and thresholds. Lastly, the experiment results show FFPgrowth algorithm is more efficient than other existing methods.

A New IT-Convergence Service Design Framework

In many countries, digital city or ubiquitous city (u-City) projects have been initiated to provide digitalized economic environments to cities. Recently in Korea, Kangwon Province has started the u-Kangwon project to boost local economy with digitalized tourism services. We analyze the limitations of the ubiquitous IT approach through the u-Kangwon case. We have found that travelers are more interested in quality over speed in access of information. For improved service quality, we are looking to develop an IT-convergence service design framework (ISDF). The ISDF is based on the service engineering technique and composed of three parts: Service Design, Service Simulation, and the Service Platform.

Philosophy of Education: The Challenges of Globalization and Innovation in the Information Society

Information society is an absolutely new public formation at which the infrastructure and the social relations correspond to the socialized essence of «information genotype» mankind. Information society is a natural social environment which allows the person to open completely the information nature, to use intelligence for joint creation with other people of new information on the basis of knowledge earlier saved up by previous generations.

Effect of Co3O4 Nanoparticles Addition on (Bi,Pb)-2223 Superconductor

The effect of nano Co3O4 addition on the superconducting properties of (Bi, Pb)-2223 system was studied. The samples were prepared by the acetate coprecipitation method. The Co3O4 with different sizes (10-30 nm and 30-50 nm) from x=0.00 to 0.05 was added to Bi1.6Pb0.4Sr2Ca2Cu3Oy(Co3O4)x. Phase analysis by XRD method, microstructural examination by SEM and dc electrical resistivity by four point probe method were done to characterize the samples. The X-ray diffraction patterns of all the samples indicated the majority Bi-2223 phase along with minor Bi-2212 and Bi-2201 phases. The volume fraction was estimated from the intensities of Bi- 2223, Bi-2212 and Bi-2201 phase. The sample with x=0.01 wt% of the added Co3O4 (10-30 nm size) showed the highest volume fraction of Bi-2223 phase (72%) and the highest superconducting transition temperature, Tc (~102 K). The non-added sample showed the highest Tc(~103 K) compared to added samples with nano Co3O4 (30-50 nm size) added samples. Both the onset critical temperature Tc(onset) and zero electrical resistivity temperature Tc(R=0) were in the range of 103-115 ±1K and 91-103 ±1K respectively for samples with added Co3O4 (10-30 nm and 30-50 nm).

Cyber Warriors for Cyber Security and Information Assurance- An Academic Perspective

A virtualized and virtual approach is presented on academically preparing students to successfully engage at a strategic perspective to understand those concerns and measures that are both structured and not structured in the area of cyber security and information assurance. The Master of Science in Cyber Security and Information Assurance (MSCSIA) is a professional degree for those who endeavor through technical and managerial measures to ensure the security, confidentiality, integrity, authenticity, control, availability and utility of the world-s computing and information systems infrastructure. The National University Cyber Security and Information Assurance program is offered as a Master-s degree. The emphasis of the MSCSIA program uniquely includes hands-on academic instruction using virtual computers. This past year, 2011, the NU facility has become fully operational using system architecture to provide a Virtual Education Laboratory (VEL) accessible to both onsite and online students. The first student cohort completed their MSCSIA training this past March 2, 2012 after fulfilling 12 courses, for a total of 54 units of college credits. The rapid pace scheduling of one course per month is immensely challenging, perpetually changing, and virtually multifaceted. This paper analyses these descriptive terms in consideration of those globalization penetration breaches as present in today-s world of cyber security. In addition, we present current NU practices to mitigate risks.

Systematic Study of the p, d and 3He Elastic Scattering on 6Li

the elastic scattering of protons, deuterons and 3He on 6Li at different incident energies have been analyzed in the framework of the optical model using ECIS88 as well as SPI GENOA codes. The potential parameters were extracted in the phenomenological treatment of measured by us angular distributions and literature data. A good agreement between theoretical and experimental differential cross sections was obtained in whole angular range. Parameters for real part of potential have been also calculated microscopically with singleand double-folding model for the p and d, 3He scattering, respectively, using DFPOT code. For best agreement with experiment the normalization factor N for the potential depth is obtained in the range of 0.7-0.9.

Identification of Flexographic-printed Newspapers with NIR Spectral Imaging

Near-infrared (NIR) spectroscopy is a widely used method for material identification for laboratory and industrial applications. While standard spectrometers only allow measurements at one sampling point at a time, NIR Spectral Imaging techniques can measure, in real-time, both the size and shape of an object as well as identify the material the object is made of. The online classification and sorting of recovered paper with NIR Spectral Imaging (SI) is used with success in the paper recycling industry throughout Europe. Recently, the globalisation of the recycling material streams caused that water-based flexographic-printed newspapers mainly from UK and Italy appear also in central Europe. These flexo-printed newspapers are not sufficiently de-inkable with the standard de-inking process originally developed for offset-printed paper. This de-inking process removes the ink from recovered paper and is the fundamental processing step to produce high-quality paper from recovered paper. Thus, the flexo-printed newspapers are a growing problem for the recycling industry as they reduce the quality of the produced paper if their amount exceeds a certain limit within the recovered paper material. This paper presents the results of a research project for the development of an automated entry inspection system for recovered paper that was jointly conducted by CTR AG (Austria) and PTS Papiertechnische Stiftung (Germany). Within the project an NIR SI prototype for the identification of flexo-printed newspaper has been developed. The prototype can identify and sort out flexoprinted newspapers in real-time and achieves a detection accuracy for flexo-printed newspaper of over 95%. NIR SI, the technology the prototype is based on, allows the development of inspection systems for incoming goods in a paper production facility as well as industrial sorting systems for recovered paper in the recycling industry in the near future.

Reliability of Digital FSO Links in Europe

The paper deals with an analysis of visibility records collected from 210 European airports to obtain a realistic estimation of the availability of Free Space Optical (FSO) data links. Commercially available optical links usually operate in the 850nm waveband. Thus the influence of the atmosphere on the optical beam and on the visible light is similar. Long-term visibility records represent an invaluable source of data for the estimation of the quality of service of FSO links. The model used characterizes both the statistical properties of fade depths and the statistical properties of individual fade durations. Results are presented for Italy, France, and Germany.

Towards a Unified Approach of Social Justice: Merging Tradition and Modernity in Public Policy Making in India

This paper explores the social and political imperatives in the sphere of public policy relating to social justice. In India, the colonial legacy and post-colonial social and political pressures sustained the appropriation of 'caste' category in allocating public resources to the backward class of citizens. For several reasons, 'economic' category could not be placed in allocating resources. This paper examines the reasons behind the deliberative exercises and formulating policies and seeks an alternative framework in realizing social justice in terms of a unified category. This attempt can be viewed as a reconciliation of traditional and modern values for a viable alternative in public policy making.

Genetic-Based Multi Resolution Noisy Color Image Segmentation

Segmentation of a color image composed of different kinds of regions can be a hard problem, namely to compute for an exact texture fields. The decision of the optimum number of segmentation areas in an image when it contains similar and/or un stationary texture fields. A novel neighborhood-based segmentation approach is proposed. A genetic algorithm is used in the proposed segment-pass optimization process. In this pass, an energy function, which is defined based on Markov Random Fields, is minimized. In this paper we use an adaptive threshold estimation method for image thresholding in the wavelet domain based on the generalized Gaussian distribution (GGD) modeling of sub band coefficients. This method called Normal Shrink is computationally more efficient and adaptive because the parameters required for estimating the threshold depend on sub band data energy that used in the pre-stage of segmentation. A quad tree is employed to implement the multi resolution framework, which enables the use of different strategies at different resolution levels, and hence, the computation can be accelerated. The experimental results using the proposed segmentation approach are very encouraging.

A Systems Modeling Approach to Support Environmentally Sustainable Business Development in Manufacturing SMEs

Small and Medium Sized Enterprises (SMEs) play an important role in many economies. In New Zealand, for example, 97% of all manufacturing companies employ less than 100 staff, and generate the predominant part of this industry sector-s economic output. Manufacturing SMEs as a group also have a significant impact on the environment. This situation is similar in many developed economies, including the European Union. Sustainable economic development therefore needs to strongly consider the role of manufacturing SMEs, who generally find it challenging to move towards more environmentally friendly business practices. This paper presents a systems thinking approach to modelling and understanding the factors which have an influence on the successful uptake of environmental practices in small and medium sized manufacturing companies. It presents a number of causal loop diagrams which have been developed based on primary action research, and a thorough understanding of the literature in this area. The systems thinking model provides the basis for further development of a strategic framework for the successful uptake of environmental innovation in manufacturing SMEs.

Optical Limiting Characteristics of Core-Shell Nanoparticles

TiO2 nanoparticles were synthesized by hydrothermal method at 180°C from TiOSO4 aqueous solution with1m/l concentration. The obtained products were coated with silica by means of a seeded polymerization technique for a coating time of 1440 minutes to obtain well defined TiO2@SiO2 core-shell structure. The uncoated and coated nanoparticles were characterized by using X-Ray diffraction technique (XRD), Fourier Transform Infrared Spectroscopy (FT-IR) to study their physico-chemical properties. Evidence from XRD and FTIR results show that SiO2 is homogenously coated on the surface of titania particles. FTIR spectra show that there exists an interaction between TiO2 and SiO2 and results in the formation of Ti-O-Si chemical bonds at the interface of TiO2 particles and SiO2 coating layer. The non linear optical limiting properties of TiO2 and TiO2@SiO2 nanoparticles dispersed in ethylene glycol were studied at 532nm using 5ns Nd:YAG laser pulses. Three-photon absorption is responsible for optical limiting characteristics in these nanoparticles and it is seen that the optical nonlinearity is enhanced in core-shell structures when compared with single counterparts. This effective three-photon type absorption at this wavelength, is of potential application in fabricating optical limiting devices.

Quantitative Estimation of Periodicities in Lyari River Flow Routing

The hydrologic time series data display periodic structure and periodic autoregressive process receives considerable attention in modeling of such series. In this communication long term record of monthly waste flow of Lyari river is utilized to quantify by using PAR modeling technique. The parameters of model are estimated by using Frances & Paap methodology. This study shows that periodic autoregressive model of order 2 is the most parsimonious model for assessing periodicity in waste flow of the river. A careful statistical analysis of residuals of PAR (2) model is used for establishing goodness of fit. The forecast by using proposed model confirms significance and effectiveness of the model.

A Comparison Study of the Removal of Selected Pharmaceuticals in Waters by Chemical Oxidation Treatments

The degradation of selected pharmaceuticals in some water matrices was studied by using several chemical treatments. The pharmaceuticals selected were the beta-blocker metoprolol, the nonsteroidal anti-inflammatory naproxen, the antibiotic amoxicillin, and the analgesic phenacetin; and their degradations were conducted by using UV radiation alone, ozone, Fenton-s reagent, Fenton-like system, photo-Fenton system, and combinations of UV radiation and ozone with H2O2, TiO2, Fe(II), and Fe(III). The water matrices, in addition to ultra-pure water, were a reservoir water, a groundwater, and two secondary effluents from two municipal WWTP. The results reveal that the presence of any second oxidant enhanced the oxidation rates, with the systems UV/TiO2 and O3/TiO2 providing the highest degradation rates. It is also observed in most of the investigated oxidation systems that the degradation rate followed the sequence: amoxicillin > naproxen > metoprolol > phenacetin. Lower rates were obtained with the pharmaceuticals dissolved in natural waters and secondary effluents due to the organic matter present which consume some amounts of the oxidant agents.