Design parameters for earth-wire power tapping

The paper deals with the calculation of the induced voltage on, and the equivalent capacitance of, an earth wire isolated for purposes of tapping small amounts of power from high-voltage lines. The influence of heights, diameters and spacings of conductors on these quantities have been studied and presented in the form of graphs.

Bipartite Powers of k-chordal Graphs

Let k be an integer and k >= 3. A graph G is k-chordal if G does not have an induced cycle of length greater than k. From the definition it is clear that 3-chordal graphs are precisely the class of chordal graphs. Duchet proved that, for every positive integer m, if G m is chordal then so is G(m+2). Brandst `` adt et al. in Andreas Brandsadt, Van Bang Le, and Thomas Szymczak. Duchet- type theorems for powers of HHD- free graphs. Discrete Mathematics, 177(1- 3): 9- 16, 1997.] showed that if G m is k - chordal, then so is G(m+2). Powering a bipartite graph does not preserve its bipartitedness. In order to preserve the bipartitedness of a bipartite graph while powering Chandran et al. introduced the notion of bipartite powering. This notion was introduced to aid their study of boxicity of chordal bipartite graphs. The m - th bipartite power G(m]) of a bipartite graph G is the bipartite graph obtained from G by adding edges (u; v) where d G (u; v) is odd and less than or equal to m. Note that G(m]) = G(m+1]) for each odd m. In this paper we show that, given a bipartite graph G, if G is k-chordal then so is G m], where k, m are positive integers with k >= 4

Rainbow Connection Number of Graph Power and Graph Products

Rainbow connection number, rc(G), of a connected graph G is the minimum number of colors needed to color its edges so that every pair of vertices is connected by at least one path in which no two edges are colored the same (note that the coloring need not be proper). In this paper we study the rainbow connection number with respect to three important graph product operations (namely the Cartesian product, the lexicographic product and the strong product) and the operation of taking the power of a graph. In this direction, we show that if G is a graph obtained by applying any of the operations mentioned above on non-trivial graphs, then rc(G) a parts per thousand currency sign 2r(G) + c, where r(G) denotes the radius of G and . In general the rainbow connection number of a bridgeless graph can be as high as the square of its radius 1]. This is an attempt to identify some graph classes which have rainbow connection number very close to the obvious lower bound of diameter (and thus the radius). The bounds reported are tight up to additive constants. The proofs are constructive and hence yield polynomial time -factor approximation algorithms.

Boxicity and cubicity of product graphs

The boxicity (cubicity) of a graph G is the minimum natural number k such that G can be represented as an intersection graph of axis-parallel rectangular boxes (axis-parallel unit cubes) in R-k. In this article, we give estimates on the boxicity and the cubicity of Cartesian, strong and direct products of graphs in terms of invariants of the component graphs. In particular, we study the growth, as a function of d, of the boxicity and the cubicity of the dth power of a graph with respect to the three products. Among others, we show a surprising result that the boxicity and the cubicity of the dth Cartesian power of any given finite graph is, respectively, in O(log d/ log log d) and circle dot(d/ log d). On the other hand, we show that there cannot exist any sublinear bound on the growth of the boxicity of powers of a general graph with respect to strong and direct products. (C) 2015 Elsevier Ltd. All rights reserved.

Efficient Output-Sensitive Construction of Reeb Graphs

The Reeb graph tracks topology changes in level sets of a scalar function and finds applications in scientific visualization and geometric modeling. This paper describes a near-optimal two-step algorithm that constructs the Reeb graph of a Morse function defined over manifolds in any dimension. The algorithm first identifies the critical points of the input manifold, and then connects these critical points in the second step to obtain the Reeb graph. A simplification mechanism based on topological persistence aids in the removal of noise and unimportant features. A radial layout scheme results in a feature-directed drawing of the Reeb graph. Experimental results demonstrate the efficiency of the Reeb graph construction in practice and its applications.

A do-it-yourself (DIY) switched mode power conversion laboratory

In the education of physical sciences, the role of the laboratory cannot be overemphasised. It is the laboratory exercises which enable the student to assimilate the theoretical basis, verify the same through bench-top experiments, and internalize the subject discipline to acquire mastery of the same. However the resources essential to put together such an environment is substantial. As a result, the students go through a curriculum which is wanting in this respect. This paper presents a low cost alternative to impart such an experience to the student aimed at the subject of switched mode power conversion. The resources are based on an open source circuit simulator (Sequel) developed at IIT Mumbai, and inexpensive construction kits developed at IISc Bangalore. The Sequel programme developed by IIT Mumbai, is a circuit simulation program under linux operating system distributed free of charge. The construction kits developed at IISc Bangalore, is fully documented for anyone to assemble these circuit which minimal equipment such as soldering iron, multimeter, power supply etc. This paper puts together a simple forward dc to dc converter as a vehicle to introduce the programming under sequel to evaluate the transient performance and small signal dynamic model of the same. Bench tests on the assembled construction kit may be done by the student for study of operation, transient performance and closed loop stability margins etc.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

On the cubicity of bipartite graphs

A unit cube in k-dimension (or a k-cube) is defined as the Cartesian product R-1 x R-2 x ... x R-k, where each R-i is a closed interval on the real line of the form [a(j), a(i), + 1]. The cubicity of G, denoted as cub(G), is the minimum k such that G is the intersection graph of a collection of k-cubes. Many NP-complete graph problems can be solved efficiently or have good approximation ratios in graphs of low cubicity. In most of these cases the first step is to get a low dimensional cube representation of the given graph. It is known that for graph G, cub(G) <= left perpendicular2n/3right perpendicular. Recently it has been shown that for a graph G, cub(G) >= 4(Delta + 1) In n, where n and Delta are the number of vertices and maximum degree of G, respectively. In this paper, we show that for a bipartite graph G = (A boolean OR B, E) with |A| = n(1), |B| = n2, n(1) <= n(2), and Delta' = min {Delta(A),Delta(B)}, where Delta(A) = max(a is an element of A)d(a) and Delta(B) = max(b is an element of B) d(b), d(a) and d(b) being the degree of a and b in G, respectively , cub(G) <= 2(Delta' + 2) bar left rightln n(2)bar left arrow. We also give an efficient randomized algorithm to construct the cube representation of G in 3 (Delta' + 2) bar right arrowIn n(2)bar left arrow dimension. The reader may note that in general Delta' can be much smaller than Delta.

Latency, Power and Performance Trade-offs in Network-on-Chips by Link Microarchitecture Exploration

This paper presents a power, latency and throughput trade-off study on NoCs by varying microarchitectural (e.g. pipelining) and circuit level (e.g. frequency and voltage) parameters. We change pipelining depth, operating frequency and supply voltage for 3 example NoCs - 16 node 2D Torus, Tree network and Reduced 2D Torus. We use an in-house NoC exploration framework capable of topology generation and comparison using parameterized models of Routers and links developed in SystemC. The framework utilizes interconnect power and delay models from a low-level modelling tool called Intacte[1]1. We find that increased pipelining can actually reduce latency. We also find that there exists an optimal degree of pipelining which is the most energy efficient in terms of minimizing energy-delay product.

Cubicity of threshold graphs

We show that the cubicity of a connected threshold graph is equal to inverted right perpendicularlog(2) alpha inverted left perpendicular, where alpha is its independence number.

Fast Multiple Access Selection through variable power transmissions

Many wireless applications demand a fast mechanism to detect the packet from a node with the highest priority ("best node") only, while packets from nodes with lower priority are irrelevant. In this paper, we introduce an extremely fast contention-based multiple access algorithm that selects the best node and requires only local information of the priorities of the nodes. The algorithm, which we call Variable Power Multiple Access Selection (VP-MAS), uses the local channel state information from the accessing nodes to the receiver, and maps the priorities onto the receive power. It is based on a key result that shows that mapping onto a set of discrete receive power levels is optimal, when the power levels are chosen to exploit packet capture that inherently occurs in a wireless physical layer. The VP-MAS algorithm adjusts the expected number of users that contend in each step and their respective transmission powers, depending on whether previous transmission attempts resulted in capture, idle channel, or collision. We also show how reliable information regarding the total received power at the receiver can be used to improve the algorithm by enhancing the feedback mechanism. The algorithm detects the packet from the best node in 1.5 to 2.1 slots, which is considerably lower than the 2.43 slot average achieved by the best algorithm known to date.

On the nature of power flow equations in security analysis

The power system network is assumed to be in steady-state even during low frequency transients. However, depending on generator dynamics, and toad and control characteristics, the system model and the nature of power flow equations can vary The nature of power flow equations describing the system during a contingency is investigated in detail. It is shown that under some mild assumptions on load-voltage characteristics, the power flow equations can be decoupled in an exact manner. When the generator dynamics are considered, the solutions for the load voltages are exact if load nodes are not directly connected to each other

Characterisation of k-Variegated Graphs, k greater-than-or-equal-to 3

A graph is said to be k-variegated if its vertex set can be partitioned into k equal parts such that each vertex is adjacent to exactly one vertex from every other part not containing it. Bednarek and Sanders [1] posed the problem of characterizing k-variegated graphs. V.N. Bhat-Nayak, S.A. Choudum and R.N. Naik [2] gave the characterization of 2-variegated graphs. In this paper we characterize k-variegated graphs for k greater-or-equal, slanted 3.

Some aspects of multilevel load-frequency control of a power system

The application of multilevel control strategies for load-frequency control of interconnected power systems is assuming importance. A large multiarea power system may be viewed as an interconnection of several lower-order subsystems, with possible change of interconnection pattern during operation. The solution of the control problem involves the design of a set of local optimal controllers for the individual areas, in a completely decentralised environment, plus a global controller to provide the corrective signal to account for interconnection effects. A global controller, based on the least-square-error principle suggested by Siljak and Sundareshan, has been applied for the LFC problem. A more recent work utilises certain possible beneficial aspects of interconnection to permit more desirable system performances. The paper reports the application of the latter strategy to LFC of a two-area power system. The power-system model studied includes the effects of excitation system and governor controls. A comparison of the two strategies is also made.

Optimum Evaluation of Reactive Power Requirements in Power Distribution-Systems

This paper presents three methodologies for determining optimum locations and magnitudes of reactive power compensation in power distribution systems. Method I and Method II are suitable for complex distribution systems with a combination of both radial and ring-main feeders and having different voltage levels. Method III is suitable for low-tension single voltage level radial feeders. Method I is based on an iterative scheme with successive powerflow analyses, with formulation and solution of the optimization problem using linear programming. Method II and Method III are essentially based on the steady state performance of distribution systems. These methods are simple to implement and yield satisfactory results comparable with the results of Method I. The proposed methods have been applied to a few distribution systems, and results obtained for two typical systems are presented for illustration purposes.