Network analysis methods

A commonly used network analysis method is loop and mesh analysis, which is generally based on KVL. As defined previously, loop analysis refers to the general method of current analysis for both planar and non-planar networks, whereas mesh analysis is reserved for the analysis of planar networks. In loop or mesh analysis, the circulating currents are selected as the unknowns, and a circulating current is assigned to each independent loop or mesh of the network. Then a series of equations can be formed according to KVL. 

Wasserman, S. Faust, K. (1994). Social network analysis methods and applications. In Structural analysis in the social sciences, Cambridge University Press, Cambridge,... 

Neural-network analysis methods were used to discriminate more than 50 different kinds of plastic patterns [328] and to separate PE grades [329], Shimoyama et al. [330] have recently reported discrimination of five HDPE, six LLDPE and seven LDPE grades by NIRS and chemometric analysis. PLS regression has enabled to propose good calibration models which predict the density, crystallinity and melting points of PE by use of NIR spectra. This allows use of vibrational spectroscopy... 

A technique widely used by the industry is Critical Path Analysis (CPA or Network Analysis ) which is a method for systematically analysing the schedule of large projects, so that activities within a project can be phased logically, and dependencies identified. All activities are given a duration and the longest route through the network is known as the critical path. 

All MS technologies require the establishment of method-specific mass libraries so that compounds in the spectra can be identified [212], a tedious task that has been restricted to large laboratories. Nevertheless, some of these efforts are driven by the metabolomics community, thereby requiring some sort of standardization to conduct comparable experiments, as has been proposed with the ArMet standard [216], Last but not the least, metabolomics experiments generate large amounts of data that need sophisticated analysis methods to extract biological information, usually based on multidimensional statistics [3, 5, 58, 209, 217, 218]. Metabolomics experiments as the basis for an analysis of the possible dynamics of metabolic networks are discussed in Section VIII. 

Protocol analysis. Protocol analysis is the process of capturing, decoding, and interpreting electronic traffic. The protocol analysis method of network intrusion detection involves the analysis of data captured during transactions between two or more systems or devices, and the evaluation of these data to identify unusual activity and potential problems. Once a problem is isolated and recorded, problems or potential threats can be linked to pieces of hardware or software. Sophisticated protocol analysis will also provide statistics and trend information on the captured traffic. 

Many of the hotplate devices presented so far rely on corresponding thermal simulations that are based on model assumptions and hnite element methods (FEM) [47, 92-97]. Analytical models also have been developed [7,9,98,99] another publication describes RC-network analysis and dimension reduction [100]. A reduction of the complexity and order of the model has been successfully realized, and the dilFerent relevant approaches have been summarized in recent articles [101,102]... 

Prior Applications. The first application of this traditional factor analysis method was an attempt by Blifford and Meeker (6) to interpret the elemental composition data obtained by the National Air Sampling Network(NASN) during 1957-61 in 30 U.S. cities. They employed a principal components analysis and Varimax rotation as well as a non-orthogonal rotation. In both cases, they were not able to extract much interpretable information from the data. Since there is a very wide variety of sources of particles in 30 cities and only 13 elements measured, it is not surprising that they were unable to provide much specificity to their factors. One interesting factor that they did identify was a copper factor. They were unable to provide a convincing interpretation. It is likely that this factor represents the copper contamination from the brushes of the high volume air samples that was subsequently found to be a common problem ( 2). 

H.W. Bode, Network Analysis and Feedback Amplifier Design, Van Nostrand, NY (1945) 6) Greenwood and Collaborators, Electronic Instruments, vol 21, MIT Radiation Laboratory Series, McGraw Hill, NY (1948) 7) R.H. Muller, AnalChem 20, 389 (1948) (Instrumental methods of analysis)... 

A generalised structure of an electronic nose is shown in Fig. 15.9. The sensor array may be QMB, conducting polymer, MOS or MS-based sensors. The data generated by each sensor are processed by a pattern-recognition algorithm and the results are then analysed. The ability to characterise complex mixtures without the need to identify and quantify individual components is one of the main advantages of such an approach. The pattern-recognition methods maybe divided into non-supervised (e.g. principal component analysis, PCA) and supervised (artificial neural network, ANN) methods also a combination of both can be used. 

These results clearly indicate that the multi-frequency dynamic analysis method allows us to estimate the contribution of different relaxation mechanisms during curing of elastomers, and the changes in chemical and physical networks densities can be studied separately. 

KNN)13 14 and potential function methods (PFMs).15,16 Modeling methods establish volumes in the pattern space with different bounds for each class. The bounds can be based on correlation coefficients, distances (e.g. the Euclidian distance in the Pattern Recognition by Independent Multicategory Analysis methods [PRIMA]17 or the Mahalanobis distance in the Unequal [UNEQ] method18), the residual variance19,20 or supervised artificial neural networks (e.g. in the Multi-layer Perception21). 

Chapter 4 covers the site selection and site controlling phase. Consequently, it deals with the assessment of individual production sites based on primarily qualitative criteria. Alternative Multiple Attribute Decision Analysis methods are reviewed and a decision support model employing the Analytic Hierarchy Process, which can be used both for site selection problems and as a controlling tool to perform site portfolio rankings of entire production networks, is proposed. Experiences from application in industry are reported. 

C. Gutfinger, E. Broyer, and Z. Tadmor, Analysis of a Cross Head Film Blowing Die with the Flow Analysis Network (FAN) Method, Polym. Eng. Sci., 15, 385-386 (1975). 

Example 15.3 The Flow Analysis Network Method Clearly Eq. E15.2-22 is identical to Eq. E15.2-21. This is the basis for the flow analysis network (FAN) method developed by Tadmor et al. (30) to solve two-dimensional steady or quasi-steady state flow problems in injection molds and extrusion dies. In two-dimensional flows the pressure distribution is obtained by dividing the flow region into an equal-sized mesh of square elements... 

Klamt, S. Schuster, S. et al. Comparison of network-based pathway analysis methods. Trends Biotechnol 2004, 22 400-405. 

This paper presents a thermodynamic availability analysis of an important process design problem, namely, the synthesis of networks of exchangers, heaters and/or coolers to transfer the excess energy from a set of hot streams to streams which require heating (cold streams). Emphasis is placed on the discussion of thermodynamic and economic (i.e., thermoeconomic) aspects of two recent methods for the evolutionary synthesis of energy-optimum and minimum-cost networks. These methods include the... 

Awad, T.S., and Marangoni, A.G. (2005). Comparison between image analysis methods for the determination of the Iractal dimension of fat crystal networks. In Fat Crystal Networks, A.G. Marangoni (ed.). Marcel Dekker, New York. 

One of the tasks that can be accomplished relatively easily in flow analysis is the creation of conditions that allow a series of measurement results to be obtained using only a single standard solution (and not several standard solutions). A classic example is the network calibration method, performed using a flow system made up of a network of tubes of different lengths connected to each other prior to the detector (Fig. 3.10a) [6]. In this system, the injected segment of standard solution is... 

Chemometric methods such as analysis of correlation coefficients, cluster analysis or neural network analysis are used, for example, in the classification of fragments of glass on the basis of their elemental composition or refractive index. Such methods allow the test material to be classified into the appropriate group of products on the basis of the measured parameter. 

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