Satellite-based water quality monitoring in Lake Vänern,Sweden

Lake Vänern, Sweden, is one of Europe’s largest lakes and has a historical, cultural, ecological as well as economic importance. Lake water quality monitoring is required by national and international legislations and directives, but present programmes are insufficient to meet the requirements. To complement in situ based monitoring, the possibility to obtain reliable information about spatial and temporal water quality trends in Lake Vänern from the ENVISAT mission’s MERIS instrument was evaluated. The complete archive (2002–2012) of MERIS (Medium Resolution Imaging Spectrometer) full resolution data was processed using the water processor developed by Free University Berlin (FUB) to derive aerosol optical thickness (AOT), remote-sensing reflectance (R_rs) and water quality parameters: chlorophyll-a (chl-a) concentration, coloured dissolved organic matter absorption at 443 nm (CDOM), and total suspended matter (TSM) concentration. The objective was to investigate if, either, FUB reflectance products in combination with potential lake-specific band ratio algorithms for water quality estimation, or directly, FUB water quality products, could complement the existing monitoring programme.

Application of lake-specific band ratio algorithms requires high-quality reflectance products based on correctly estimated AOT. The FUB reflectance and AOT products were evaluated using Aerosol Robotic Network – Ocean Color (AERONET-OC) match-up data measured at station Pålgrunden in Lake Vänern. The mean absolute percentage differences (MAPDs) of the final reflectance retrievals at 413, 443, 490, 555, and 665 nm were 510%, 48%, 33%, 34%, and 33%, respectively, corresponding to a large positive bias in 413 nm, positive bias in 443–555 nm, and a negative bias in 665 nm. AOT was strongly overestimated in all bands.

The FUB water quality products were evaluated using match-up in situ data of chl-a, filtered absorbance (Abs_F(420)) and turbidity as Abs_F(420) is related to CDOM and turbidity is strongly related to TSM. The in situ data was collected within the Swedish national and regional monitoring programmes. In order to widen the range of water constituents and add more data to the analysis, data from four large Swedish lakes (Vänern, Vättern, Mälaren, and Hjälmaren) was included in the analysis. High correlation (r ≥ 0.85) between in situ data and MERIS FUB derived water quality estimates were obtained, but the absolute levels were over- (chl-a) or under- (CDOM) estimated. TSM was retrieved without bias.

Calibration algorithms were established for chl-a and CDOM based on the match-up data from all four lakes. After calibration of the MERIS FUB data, realistic time series could be derived that were well in line with in situ measurements. The MAPDs of the final retrievals of chl-a, Abs_F(420) and Turbidity in Lake Vänern were 37%, 15%, and 35%, respectively, corresponding to mean absolute differences (MADs) of 0.9 µg l^?1, 0.17 m^?1, and 0.32 mg l^?1 in absolute values.

The partly inaccurate reflectance estimations in combination with both positive and negative bias imply that successful application of band ratio algorithms is unlikely. The high correlation between MERIS FUB water quality products and in situ data, on the other hand, shows a potential to complement present water quality monitoring programmes and improve the understanding and representability of the temporally and spatially sparse in situ observations. The monitoring potential shown in this study is applicable to the Sentinel-3 mission’s OLCI (Ocean Land Colour Instrument), which was launched by the European Space Agency (ESA) in February 2016 as a part of the EC Copernicus programme.     

Generalization and analysis of sufficient conditions for PCA-based fault detectability and isolability

Fault detectability and fault isolability concepts are necessary to be developed in order to determine whether the process faults are detectable and isolable. In PCA framework, the development of these concepts has been limited to the use of some particular detection indices. This paper provides an extension and a generalization of the fault detectability and the reconstruction-based fault isolabilty concepts in order to be valid for the use of any detection index having a quadratic-form. Fundamental fault detectability as well as fault isolability analyses based on the combined index compared to those using both SPE and Hotelling’s T2 indices are investigated. In addition, we have illustrated the proposed analyses from a simulation example. This one highlights the advantage of the combined index into the isolation of some process faults that have not large enough magnitudes to be isolable neither by SPE index nor by Hotelling’s T2 statistic.     

Corrigendum to “Complex flow simulation in natural aquifer” [Adv. Eng. Inform. 23 (2009) 288–293]: An algorithm for parallel flow simulations in the finite element framework

The high advanced techniques in parallel computing can be employed for a better understanding of groundwater flow fluids. Generally, the geological media are very heterogeneous and contain complex structures. Decomposing these structures into, approximately, equivalent sub-structures for a load-balancing is a major challenge. This paper proposes and analyses a new algorithm to simulate parallel flow fluid in such complex media. Fully parallel software is developed, and two well-known sparse linear solvers, based respectively on a multifrontal Cholesky factorization and an iterative structured multigrid method, are compared. The mixed finite element (MFE) method is used to discretize Darcy’s equation. Numerical examples are presented to show the efficiency and robustness of the algorithm proposed.     

LMI solutions for H-two and H-infinity decentralized controllers applied to an aerothermic process

In this paper, we present a linear matrix inequality (LMI)-based solution to implement H-two and Hinfinity decentralized robust control strategies. Appropriate parametrization of optimal H-two and H-infinity controllers is used. The general formulation of the decentralized control design leads to the optimal determination of both the state feedback gains and the observer gains of the decentralized controllers. This formulation is two folds: first, a centralized controller is obtained, and then, a simplified decentralized solution is derived by optimizing only the observer gains. The mathematical determination of these gains is formulated as an LMI optimization problem that can be easily solved using LMI solvers. As an experimental evaluation of these controllers, a real time application to an aerothermic process is carried out. A continuous-time model of the process obtained with a suitable direct continuous-time identification approach is elaborated. Results illustrating the real performance obtained from the H-two and H-infinity decentralized controllers are discussed and compared with the centralized ones.     

A review: accuracy optimization in clustering ensembles using genetic algorithms

The clustering ensemble has emerged as a prominent method for improving robustness, stability, and accuracy of unsupervised classification solutions. It combines multiple partitions generated by different clustering algorithms into a single clustering solution. Genetic algorithms are known as methods with high ability to solve optimization problems including clustering. To date, significant progress has been contributed to find consensus clustering that will yield better results than existing clustering. This paper presents a survey of genetic algorithms designed for clustering ensembles. It begins with the introduction of clustering ensembles and clustering ensemble algorithms. Subsequently, this paper describes a number of suggested genetic-guided clustering ensemble algorithms, in particular the genotypes, fitness functions, and genetic operations. Next, clustering accuracies among the genetic-guided clustering ensemble algorithms is compared. This paper concludes that using genetic algorithms in clustering ensemble improves the clustering accuracy and addresses open questions subject to future research.     

Efficient prime-based method for interactive mining of frequent patterns

Over the past decade, an increasing number of efficient algorithms have been proposed to mine frequent patterns by satisfying the minimum support threshold. Generally, determining an appropriate value for minimum support threshold is extremely difficult. This is because the appropriate value depends on the type of application and expectation of the user. Moreover, in some real-time applications such as web mining and e-business, finding new correlations between patterns by changing the minimum support threshold is needed. Since rerunning mining algorithms from scratch is very costly and time-consuming, researchers have introduced interactive mining of frequent patterns. Recently, a few efficient interactive mining algorithms have been proposed, which are able to capture the content of transaction database to eliminate possibility of the database rescanning. In this paper, we propose a new method based on prime number and its characteristics mainly for interactive mining of frequent patterns. Our method isolates the mining model from the mining process such that once the mining model is constructed; it can be frequently used by mining process with various minimum support thresholds. During the mining process, the mining algorithm reduces the number of candidate patterns and comparisons by using a new candidate set called candidate head set and several efficient pruning techniques. The experimental results verify the efficiency of our method for interactive mining of frequent patterns.     

Staphylococcus aureus nasal carriage in a Moroccan dialysis center and isolates characterization

Staphylococcus aureus, which has its ecological niche in the anterior nares, has been shown to cause a variety of infectious diseases mainly for patients in hemodialysis units. We performed this study to evaluate the prevalence of nasal S. aureus carriage among hemodialysis outpatients, to determine the antimicrobial susceptibility of isolates, to characterize the virulence genes, and to identify associated risk factors. Nares swab specimens were obtained from 70 outpatients on hemodialysis between March and June 2010. Samples were plated immediately onto S. aureus specific media and pattern of antibacterial sensitivity was determined using disk diffusion method. Polymerase chain reaction was used to detect nuc, mecA, and genes encoding staphylococcal toxins. Medical record of patients was explored to determine S.aureus carriage risk factors. Nasal screening identified 42.9% S. aureus carriers with only one (3.3%) methicillin‐resistant S. aureus isolate. Among the methicillin‐susceptible S. aureus isolates, high rate of penicillin resistance (81.8%) has been detected. The identified risk factors were male gender and age ≤ 30 years. Research of virulence factors showed a high genetic diversity among the 30 S. aureus isolates. Twenty‐one (70%) of them had at least one virulence gene, of which 3.3% were Panton‐Valentine leukocidin (lukS/F‐PV) genes. S. aureus carriage must be screened for at regular intervals in hemodialysis patients. Setting up a bacterial surveillance system is one of the strategies to understand the epidemiology of methicillin‐resistant S. aureus, to guide local antibiotic policy and prevent spread of antibiotic‐resistant S. aureus.     

Stability of single-walled carbon nanotubes and single-walled carbon nanocones under self-weight and an axial tip force

Poorly designed structures buckle under the action of an unbearable axial force, self-weight or a combination of different axial forces. The increasing exploration of nanostructures for future devices dictates that the buckling of uniform single-walled carbon nanotubes (SWCNTs) and single-walled carbon nanocones (SWCNCs) should be well studied. Therefore in this paper, the investigation of the boundary value problems associated with the buckling of the SWCNTs and SWCNCs is carried out. The theoretical formulation of the mathematical model for these nanostructures is premised on the newly advanced nonlocal continuum theory. Predictions of the nN range critical loads of SWCNT and SWCNT under self-weight and an axial tip force are carried out with an optimized variant of the Galerkin method. The analysis reveals the degree of influence of the nonlocal parameter on the critical loads of the SWCNTs and the SWCNCs under different boundary conditions. A non-monotonically increasing trend is observed between the critical load values and increasing aspect ratio of the SWCNT. In the case of the SWCNC, the analysis reveals a positive linear relationship between the critical loads and the apex angles of the SWCNC. The apex angle also acts as a counterbalance to the small-scale coefficient.