A novel method of network function analysis based on the Andreani–Mattisson extension to the Cochrun–Grabel algorithm

Mapping network nodes and edges to communities and network functions is crucial to gaining a higher level of understanding of the network structure and functions. Such mappings are particularly challenging to design for covert social networks, which intentionally hide their structure and functions to protect important members from attacks or arrests. Here, we focus on correctly inferring the structures and functions of such networks, but our methodology can be broadly applied. Without the ground truth, knowledge about the allocation of nodes to communities and network functions, no single network based on the noisy data can represent all plausible communities and functions of the true underlying network. To address this limitation, we apply a generative model that randomly distorts the original network based on the noisy data, generating a pool of statistically equivalent networks. Each unique generated network is recorded, while each duplicate of the already recorded network just increases the repetition count of that network. We treat each such network as a variant of the ground truth with the probability of arising in the real world approximated by the ratio of the count of this network's duplicates plus one to the total number of all generated networks. Communities of variants with frequently occurring duplicates contain persistent patterns shared by their structures. Using Shannon entropy, we can find a variant that minimizes the uncertainty for operations planned on the network. Repeatedly generating new pools of networks from the best network of the previous step for several steps lowers the entropy of the best new variant. If the entropy is too high, the network operators can identify nodes, the monitoring of which can achieve the most significant reduction in entropy. Finally, we also present a heuristic for constructing a new variant, which is not randomly generated but has the lowest expected cost of operating on the distorted mappings of network nodes to communities and functions caused by noisy data.

A symbolic linear analyzer that integrates the analysis of both lumped and distributed networks is presented in this paper. This is achieved by implementing a consistent set of notations and a unified mathematical framework. The merits of sparse symbolic matrices are utilized to develop a complete symbolic sparse toolbox that includes all basic elements of electrical circuits. A new storage scheme called Row-Indexed Semi-Symetric (RISS) sparse is proposed and implemented for symbolic network matrices. Several existing and newly developed matrix solvers are implemented and their performances are compared. These solvers are used in the proposed symbolic solver to provide a multi-path analysis root that can be optimized for a particular problem. The overall performance of the proposed symbolic analyzer is assessed practically using several application examples. The obtained results are found in agreement with the results obtained from previously reported analyses and thus confirm validity of the adopted formula approximation method. A polynomial fitting shows that the time complexity of a variable size RC network is super-quadratic with the number of network sections. A substantial reduction in the analysis time of a large ladder RC network is demonstrated with the implementation of macromodeling techniques.KeywordsSymbolic analysissymbolic matrix storagelumped and distributed network analysisoptimal computer solution

This paper presents a new approach to symbolic network analysis. The procedure is entirely topology oriented because it operates with a netlist description of the analyzed circuit. The obtained network function has nested form. The method introduces a graph representation of the factorization process, that is constructed directly from a given circuit description. Therefore, it is named Topology Decision Diagram (TDD). This graph serves as a skeleton for network function generation. TDD construction starts from the original circuit and spreads to simplified subcircuits. Every subsequent subcircuit is obtained by replacing a circuit branch with an open or a short. The proposed procedure generates the network function in reverse order. It starts from a single circuit parameter placed as a leaf of TDD. Thereafter, the circuit function grows instantiating the other circuit parameter one by one in a sequential order. The proposed method was developed for analogue CMOS circuits and, consequently, recognizes R, L, C and gm as circuit components.

LINEAR CIRCUIT ANALYSIS. Fundamental Circuit Concepts. Network Laws and Theorems. Terminal and Port Representation. Signal Flow Graphs in Filter Analysis and Synthesis. Analysis in the Frequency Domain. Tableau and Modified Nodal Formulations. Frequency Domain Methods. Symbolic Analysis. Analysis in the Time Domain. State-Variable Techniques. FEEDBACK CIRCUITS. Feedback Amplifier Theory. Feedback Amplifier Configurations. General Feedback Theory. The Network Functions and Feedback. Measurement of Return Difference. Multiple-Loop Feedback Amplifiers. Index.

By using Network Function Virtualization (NFV), several kinds of network functions can be provided in commercial off-the-shelf (COTS) servers. Such network function is called Virtual Network Function (VNF). In terms of the utilization of VNFs, an emerging technology called service chaining enables network operators to provide network services dynamically and flexibly. Here, the number of VNF instances should be managed dynamically according to the amount of traffic. In this paper, we propose a dynamic management of VNF instances with Model Predictive Control (MPC) for multiple service chains. In the proposed method, the number of VNF instances is changed dynamically according to the predicted amount of traffic. We evaluate the performance of the proposed method and threshold method with simulation. In numerical examples, it is shown that the proposed method can avoid data loss with a small number of VNF instances.

Computational costs limit large scale reservoir simulations to coarse grid systems. Determination of an effective permeability for a simulation grid block requires a proper scale-up of small scale permeability heterogeneities within that grid block. Conventional scale-up techniques are limited to a diagonal tensor representation of effective permeability. Therefore, such techniques cannot handle general permeability anisotropy (full tensor) exemplified by cross-bedded permeability structures that may be present on a smaller scale. An analytical method is developed to calculate an effective permeability tensor for a grid block by accounting for small scale heterogeneities within the grid block. The method honors both the location and the orientation of the small scale heterogeneities. Effective permeability tensors calculated using the analytical method and a numerical method show excellent agreement. Miscible displacement simulations show that the effective permeability tensor method outperforms conventional scale-up techniques in predicting flood front locations in cases of general permeability anisotropy.

Frequency characteristics for a converter are necessary to design circuit and control parameters and they are utilized, for example, for stability analysis by the impedance method. This paper proposes an automatic formulation and analysis method, which are based on a general‐purpose simulation algorithm for the frequency analysis of an averaged power converter, based on node‐connection and model characteristic information of circuit and control elements. The general equation formulation method is extended to be able to include circuits controlled in αβ frame and characteristic expressions with αβ or dq frame. As the first application example, a three‐phase grid‐following inverter with a digital sinusoidal controller based on the complex vector theory in αβ frame is analyzed for the frequency characteristics of the output admittances. The characteristics are utilized for stability analysis by the impedance method and the inverter is assured to have passive characteristics and to be stable. As the second example, a three‐phase inverter is analyzed for its αβ and dq impedances. The proposed method is investigated for the computed results and it is validated.

Network Function Virtualization (NFV) is a paradigm that virtualizes traditional network functions and instantiates Virtual Network Functions (VNFs) as software instances separate from hardware appliances. Service Chaining (SC), seen as one of the major NFV use cases, provides customized services to users by concatenating VNFs. A VNF placement model for SC that relaxes the visit order constraints of requested VNFs has been considered. Relaxing the VNF visit order constraints reduces the number of VNFs which need to be placed in the network. However, since the model does not permit any loop within an SC path, the efficiency of utilization of computation resources deteriorates in some topologies. This paper proposes a VNF placement model for SC which minimizes the cost for placing VNFs and utilizing link capacity while allowing both relaxation of VNF visit order constraints and configuration of SC paths including loops. The proposed model determines routes of requested SC paths, which can have loops, by introducing a logical layered network generated from an original physical network. This model is formulated as an Integer Linear Programming (ILP) problem. A heuristic algorithm is introduced for the case that the ILP problem is not tractable. Simulation results show that the proposed model provides SC paths with smaller cost compared to the conventional model.

Elementary modes (EMs) and minimal cut sets (MCSs) provide important techniques for metabolic network modeling. Whereas EMs describe minimal subnetworks that can function in steady state, MCSs are sets of reactions whose removal will disable certain network functions. Effective algorithms were developed for EM computation while calculation of MCSs is typically addressed by indirect methods requiring the computation of EMs as initial step. In this contribution, we provide a method that determines MCSs directly without calculating the EMs. We introduce a duality framework for metabolic networks where the enumeration of MCSs in the original network is reduced to identifying the EMs in a dual network. As a further extension, we propose a generalization of MCSs in metabolic networks by allowing the combination of inhomogeneous constraints on reaction rates. This framework provides a promising tool to open the concept of EMs and MCSs to a wider class of applications. utz-uwe.haus@math.ethz.ch; klamt@mpi-magdeburg.mpg.de Supplementary data are available at Bioinformatics online.

The energy−dependent relaxation time has been incorporated in the study of stimulated electron−phonon−photon interactions in nondegenerate semiconductors in the presence of the external dc electric field. The Boltzmann transfer equation has been used to obtain the gain constant. The results show that the percentage change in the gain constant is ∼15% (for ql<1, Eac=3 V/cm, Ω/ω=0.1, 〈vd〉=1.5 vs) and ∼30% (for ql≳1, Eac=30 V/cm, Ω/ω=2, 〈vd〉=2.0 vs) for moderate strengths of oscillating electromagnetic field (OEF). For weak OEF (Eac<ωvs/Ωμ for ql<1 and Eac <mΩ2/qe for ql≳1), no significant percentage change is observed in the gain constant in both frequency domains.

A new and efficient algorithm for topological formulation of network functions in symbolic form for a general linear (passive or active) network is presented. This algorithm, which is based on the concept of graph partitioning developed by Dunn and Chan, has all of the advantages of the existing topological formulas, such as overcoming the problem of sign evaluation and greatly reducing the number of term cancellations and the number of topological terms. In addition, and perhaps the most important, it presents a step-by-step procedure for formulating network functions that can readily be adapted for computer implementation. Finally, it is shown that the theoretical results developed herein are most suited for sensitivity analysis of linear active networks.

The risk of sand production must be evaluated from very early stages of field development planning to select the optimum well completion, and if required, identify the appropriate sand control options. However, during the appraisal or early development stages, sand production predictions often cannot be verified against field data because the lack of sanding observations. The analysis of predicting the onset and severity of sand production generally consists of using analytical or numerical rock mechanical models and ideally calibration with field sand production data. In this paper we show how in the absence of field sanding data, reliable sanding predictions can still be achieved by combining commonly used analytical and numerical prediction methods. This approach has been validated using a brown field dataset from South East Asia with several sand producing wells and multiple pressure depleted reservoirs. The analytical method uses a poro-elastic model and core-calibrated log-derived rock strength profiles with an empirical effective rock strength factor (ESF). The ESF should be calibrated against documented field sanding observations from wells with credible formation and drawdown pressures. The numerical method uses a poro-elasto-plastic model defined from triaxial core tests. The rock failure criterion in the numerical method is based on a critical strain limit (CSL) corresponding to the failure of the inner wall of thick-walled cylinder core tests or if existing field sanding data. In the brown oil field example, both analytical and numerical methods accurately predict the onset of sanding in the sand-prone wells. The core-based CSL defined by the numerical method match very well with the field sanding data with a very small margin of error. In contrast, the default and non-calibrated ESF values commonly used in the analytical method required considerable tuning to match with the field sanding data. This suggests that the core-based CSL can be used with a reasonable confidence for sand production prediction purposes in the field and the prediction can be as reliable as field-calibrated models. After the field validation, the predictions for planned infill wells by both analytical and numerical methods were consistent and similar. The paper will show how this approach is used in two other fields from the Asia Pacific region both at appraisal stages and with no field sanding data. Both cases show that different ESF values are required to match with the numerical simulations. In the absence of field sanding observation, particularly in the early stages of field development, the use of non-calibrated default ESF values in the analytical method could lead to erroneous sanding assessment and poor sand management decisions. Application of a combined analytical and numerical sanding evaluation enhances the reliability of sand production predictions. After a calibration is obtained, either with field sanding data or calibration against numerical simulation and core-based CSL criteria, the analytical method can be used with confidence and has the added benefits of simplicity and quick realizations of various scenarios and output plotting capabilities and inputs for sand control and well completion decisions.

The paper develops tools and methods for the analysis of uncertain linear time-varying, discrete-time systems. Our considerations are concerned with the analysis of a system in the frequency domain, in particular with obtaining approximate Bode amplitude diagrams by means of two methods: one based on singular value decomposition and the other on the discrete Fourier transform (SVD-DFT). Starting with the literature review of frequency domain methods for time-varying systems, we introduce the state space model with its equivalent operator form description and the most essential definitions for the Bode diagram approximations using two methods called the spectral and the averaged transfer function, respectively. Next we analyze a system with an additive uncertainty, in particular, given as a linear combination of perturbations. Theoretical considerations are summed up and illustrated by numerical examples of applications to robot manipulators. The obtained bounds (computed by the proposed method) are compared with the results obtained by means of the MATLAB wcgain function.

This work describes a method for the synthesis of diplexers based on characteristic polynomials evaluation; the method is particularly suited when the separation between the two passbands is very small. In particular the proposed method allows the evaluation of the characteristic polynomials associated to the two filters composing the diplexer (the input node is assumed as a shunt connection of the two filters input, with the possible addition of a frequency-invariant susceptance of arbitrary value). The method offers a noticeable design flexibility as it allows the synthesis of the two composing filters independently of their connection to the duplexer; moreover the choice of the filters topology is absolutely arbitrary, being allowed general cross-coupled architectures (only the order of the two filters and the imposed transmission zeros are required). The method proposed has been verified through the design and fabrication of a diplexer for GSM base stations applications.

The location of the zeros of discrete systems characteristic polynomials with respect to the unit circle is investigated. A new sequence of symmetric polynomials of descending degrees is defined for the characteristic polynomial and the number of zeros inside and outside the unit circle is shown to be related to a certain sign variation pattern of the polynomials in the sequence. A stability table based on this sequence is presented to obtain the sought distribution of zeros. The new table is close in appearance, size, and number of arithmetic operations to the Routh table used for continuous-time system polynomials. By comparison with the table of Jury, based on the theory of Marden, Cohn, and Schur, the new table involves about half the number of entries and a corresponding significant saving in computations. The study includes a detailed consideration of all possible cases of singular conditions so that the complete information on the number of zeros inside, outside, and on the unit circle is always obtained (including some additional information on possible reciprocal pairs of zeros). Necessary and sufficient conditions for a polynomial to have all its zeros inside the unit circle are obtained as a special outcome. Other additional necessary conditions, that are useful to shorten procedures when the table is used only for testing the stability of the system, are also given.