Principal component analysis for the identification of pollution sources in mussel survey by trace metals

Summary Principal component analysis has been applied to analyze the correlation matrix obtained from a 8 × 43 data matrix. The 8 trace metals are Mn, Co, Ni, Cu, Zn, Cd, Hg, Ph, which are contained in the soft part of mussels (Mytilus galloprovincialis Lamarck). Mussels were sampled from two sites in the Gulf of Trieste. In both samples, 76–78% of the total variance is explained by the four principal components. The orthogonally rotated factor matrix indicates that Co and Ni are bonded to the first principal component and Cd and Pb to the first (site 2) or second principal component (site 1). The origin of trace metals in the soft part of mussels from the Gulf of Trieste is discussed.

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Analyse der Hauptkomponenten zur Identifizierung der Verunreinigungsursachen von Muscheln über die Spurenmetalle

Zusammenfassung Die Analyse der Hauptkomponenten wurde auf die Korrelationsmatrix, die aus der 8 × 43-Datenmatrix hervorgeht, angewandt. Diese 8 Spurenmetalle sind Mn, Co, Ni, Cu, Zn, Cd, Hg, Pb, die im Fleisch der Miesmuscheln (Mytilus galloprovincialis Lamarck) gefunden worden sind. Die Miesmuscheln stammen aus zwei Gegenden des Golfes von Triest. Vier Hauptkomponenten erklären 76–78 % der totalen Varianz der beiden Stichproben. Die orthogonale-rotierte Faktorenmatrix zeigt, daß Co und Ni an die erste Hauptkomponente und Cd und Pb an die erste (Lage 2) oder an die zweite Hauptkomponente (Lage 1) gebunden sind. Die Herkunft der Spurenmetalle im Muschelfleisch aus dem Golf von Triest wird diskutiert.

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L. Felician is the author of the statistical analysis for site 1 as a part of his thesis in Commodity Science, Faculty of Economics, University of Trieste- L. Gabrielli Favretto is the author of the statistical analysis of the data for site 2. All authors contributed to the rest of the paper     

Principal component analysis for the identification of pollution sources in mussel survey by trace metals

Principal component analysis has been applied to analyze the correlation matrix obtained from a 8 X 43 data matrix. The 8 trace metals are Mn, Co, Ni, Cu, Zn, Cd, Hg, Pb, which are contained in the soft part of mussels (Mytilus galloprovincialis Lamarck). Mussels were sampled from two sites in the Gulf of Trieste. In both samples, 76-78% of the total variance is explained by the four principal components. The orthogonally rotated factor matrix indicates that Co and Ni are bonded to the first principal component and Cd and Pb to the first (site 2) or second principal component (site 1). The origin of trace metals in the soft part of mussels from the Gulf of Trieste is discussed.     

Diagnostics and prognostics for complex systems: A review of methods and challenges

Diagnostics and prognostics have a significant role in the reliability enhancement of systems and are focused topics of active research. Engineered systems are becoming more complex and are subjected to miscellaneous failure modes that impact adversely their performability. This ever-increasing complexity makes fault diagnostics and prognostics challenging for the system-level functions. A significant number of successes have been achieved and acknowledged in some review papers; however, these reviews rarely focused on application to complex engineered systems nor provided a systematic review of diverse techniques and approaches to address the related challenges. To bridge the gap, this paper first presents a review to systematically cover the general concepts and recent development of various diagnostics and prognostics approaches, along with their strengths and shortcomings for the application of diverse engineered systems. Afterwards, given the characteristics of complex systems, the applicability of different techniques and methods that are capable to address the features of complex systems are reviewed and discussed, and some of the recent achievements in the literature are introduced. Finally, the unaddressed challenges are discussed by taking into account the characteristics of automotive systems as an example of complex systems. In addition, future development and potential research trends are offered to address those challenges. Consequently, this review provides a systematic view of the state-of-the-art and case studies with a reference value for scholars and practitioners.     

Performance evaluation of metamodelling methods for engineering problems: towards a practitioner guide

Structural and Multidisciplinary Optimization - This paper presents a hybrid reliability analysis method for structures involving random and interval variables. Firstly, the original performance...     

Validating Halstead's theory for Pascal programs

M.H. Halstead's theory (1977) has been validated for different languages, but Pascal programs seem to fit only partially with the theory. D.B. Johnston and A.M. Lister (1981) first recognized the lack of operators due to the structure of this language and proposed a modification of Halstead's formula. The article confirms their results but suggests a correction to their formula, which is particularly necessary for large programs. Experimental results, obtained by examining about 550 Pascal programs, represent the widest test to date of Halstead theory with regard to Pascal programs     

Linked hashing: An improvement of open addressing techniques for large secondary storage files

An improvement of open addressing resolution schemes for hash-based files on secondary storage is defined in this paper. Linked hashing exploits the increase in compressibility of a hash file when buckets are larger, given a fixed file allocation. Both average access times and the number of records stored can significantly improve, for large files where the ratio between the key length and the record length is much less than 1.     

Application of permutation genetic algorithm for sequential model building–model validation design of experiments

The work presented in this paper is motivated by a complex multivariate engineering problem associated with engine mapping experiments, which require efficient design of experiments (DoE) strategies to minimise expensive testing. The paper describes the development and evaluation of a Permutation Genetic Algorithm (PermGA) to enable an exploration-based sequential DoE strategy for complex real-life engineering problems. A known PermGA was implemented to generate uniform OLH DoEs, and substantially extended to support generation of model building–model validation (MB–MV) sequences, by generating optimal infill sets of test points as OLH DoEs that preserve good space-filling and projection properties for the merged MB + MV test plan. The algorithm was further extended to address issues with non-orthogonal design spaces, which is a common problem in engineering applications. The effectiveness of the PermGA algorithm for the MB–MV OLH DoE sequence was evaluated through a theoretical benchmark problem based on the Six-Hump-Camel-Back function, as well as the Gasoline Direct Injection engine steady-state engine mapping problem that motivated this research. The case studies show that the algorithm is effective in delivering quasi-orthogonal space-filling DoEs with good properties even after several MB–MV iterations, while the improvement in model adequacy and accuracy can be monitored by the engineering analyst. The practical importance of this work, demonstrated through the engine case study, is that significant reduction in the effort and cost of testing can be achieved.     

A nearly optimal Huffman technique in the microcomputer environment

Huffman compression techniques have been extensively applied in this work to a microcomputer environment. A nearly optimal operating routine is proposed, which results in better performances for file backup purposes.     

A comparison of two methods of analysing staircase fatigue test data

When the fatigue strength of components or material is tested by the staircase or up‐and‐down method, the data can be analysed in either the fatigue strength domain, which is the most popular approach, or the life domain, based on life regression models. In this paper we exploit a simple relationship between families of models in the two domains to obtain an estimate of the distribution of fatigue strength directly from a fitted life regression model. We use simulation to compare the two approaches, concluding that for estimating important features of the fatigue strength distribution the method of maximum likelihood is more effective if it is applied in the life domain. In particular, it is more robust to the choice of x_h, the step height of the staircase, provided x_h is in the range σ_X–2σ_X, where σ_X is the standard deviation of the log‐strengths. Most of our results are insensitive to the value of the initial stress amplitude. Copyright © 2007 John Wiley & Sons, Ltd.