An (O)over-tilde(mn) Gomory-Hu Tree Construction Algorithm for Unweighted Graphs

We present a fast algorithm for computing a Gomory-Hu tree or cut tree for an unweighted undirected graph G = (V, E). The expected running time of our algorithm is (O) over tilde (mc) where vertical bar E vertical bar = m and c is the maximum u-v edge connectivity, where u, v is an element of V. When the input graph is also simple (i.e., it has no parallel edges), then the u-v edge connectivity for each pair of vertices u and v is at most n - 1; so the expected run-ning time of our algorithm for simple unweighted graphs is (O) over tilde (mn). All the algorithms currently known for constructing a Gomory-Hu tree [8, 9] use n - 1 minimum s-t cut (i.e., max flow) subroutines. This in conjunction with the current fastest (O) over tilde (n(20/9)) max flow algorithm due to Karger and Levine[11] yields the current best running time of (O) over tilde (n(20/9)n) for Gomory-Hu tree construction on simple unweighted graphs with m edges and n vertices. Thus we present the first (O) over tilde (mn) algorithm for constructing a Gomory-Hu tree for simple unweighted graphs. We do not use a max flow subroutine here; we present an efficient tree packing algorithm for computing Steiner edge connectivity and use this algorithm as our main subroutine. The advantage in using a tree packing algorithm for constructing a Gomory-Hu tree is that the work done in computing a minimum Steiner cut for a Steiner set S subset of V can be reused for computing a minimum Steiner cut for certain Steiner sets S' subset of S.

Performance Study of a Centralized Concurrency Control Algorithm for Distributed Database Systems using SIMULA

The stimulation technique has gained much importance in the performance studies of Concurrency Control (CC) algorithms for distributed database systems. However, details regarding the simulation methodology and implementation are seldom mentioned in the literature. One objective of this paper is to elaborate the simulation methodology using SIMULA. Detailed studies have been carried out on a centralised CC algorithm and its modified version. The results compare well with a previously reported study on these algorithms. Here, additional results concerning the update intensiveness of transactions and the degree of conflict are obtained. The degree of conflict is quantitatively measured and it is seen to be a useful performance index. Regression analysis has been carried out on the results, and an optimisation study using the regression model has been performed to minimise the response time. Such a study may prove useful for the design of distributed database systems.

An algorithm for optimum control of static VAR compensators to meet phase-wise unbalanced reactive power demands

The operation of thyristor-controlled static VAR compensators (SVCs) at various conduction angles can be used advantageously to meet the unablanced reactive power demands in a system. However, such operation introduces harmonic currents into the AC system. This paper presents an algorithm to evaluate an optimum combination of the phase-wise reactive power generations from SVC and balanced reactive power supply from the AC system, based on the defined performance indices, namely, the telephone influence factor (TIF), the total harmonic current factor (IT) and the distortion factor (D). Results of the studies conducted on a typical distribution system are presented and discussed.

Algorithm of medication review in frail older people: Focus on minimizing the use of high-risk medications

Aim Frail older people typically suffer several chronic diseases, receive multiple medications and are more likely to be institutionalized in residential aged care facilities. In such patients, optimizing prescribing and avoiding use of high-risk medications might prevent adverse events. The present study aimed to develop a pragmatic, easily applied algorithm for medication review to help clinicians identify and discontinue potentially inappropriate high-risk medications. Methods The literature was searched for robust evidence of the association of adverse effects related to potentially inappropriate medications in older patients to identify high-risk medications. Prior research into the cessation of potentially inappropriate medications in older patients in different settings was synthesized into a four-step algorithm for incorporation into clinical assessment protocols for patients, particularly those in residential aged care facilities. Results The algorithm comprises several steps leading to individualized prescribing recommendations: (i) identify a high-risk medication; (ii) ascertain the current indications for the medication and assess their validity; (iii) assess if the drug is providing ongoing symptomatic benefit; and (iv) consider withdrawing, altering or continuing medications. Decision support resources were developed to complement the algorithm in ensuring a systematic and patient-centered approach to medication discontinuation. These include a comprehensive list of high-risk medications and the reasons for inappropriateness, lists of alternative treatments, and suggested medication withdrawal protocols. Conclusions The algorithm captures a range of different clinical scenarios in relation to potentially inappropriate medications, and offers an evidence-based approach to identifying and, if appropriate, discontinuing such medications. Studies are required to evaluate algorithm effects on prescribing decisions and patient outcomes.

On the sufficient conditions for the equality of the unassignable polynomial and Davison's fixed polynomial of strongly connected systems

In this technical note, it is established that the unassignable polynomial defined for a not strongly connected decentralized control system is not equal to Davison's fixed polynomial. This leads to a "sufficient condition" for the equality of the unassignable polynomial and Davison's fixed polynomial for strongly connected systems.

A Branch and Bound Algorithm for a Transportation Type Problem with Piecewise Linear Convex Objective Function

A branch and bound type algorithm is presented in this paper to the problem of finding a transportation schedule which minimises the total transportation cost, where the transportation cost over each route is assumed to be a piecewice linear continuous convex function with increasing slopes. The algorithm is an extension of the work done by Balachandran and Perry, in which the transportation cost over each route is assumed to beapiecewise linear discontinuous function with decreasing slopes. A numerical example is solved illustrating the algorithm.

Optimal simultaneous maximum a posterioriestimation of states, noise statistics and parameters I. Algorithm

The simultaneous state and parameter estimation problem for a linear discrete-time system with unknown noise statistics is treated as a large-scale optimization problem. The a posterioriprobability density function is maximized directly with respect to the states and parameters subject to the constraint of the system dynamics. The resulting optimization problem is too large for any of the standard non-linear programming techniques and hence an hierarchical optimization approach is proposed. It turns out that the states can be computed at the first levelfor given noise and system parameters. These, in turn, are to be modified at the second level.The states are to be computed from a large system of linear equations and two solution methods are considered for solving these equations, limiting the horizon to a suitable length. The resulting algorithm is a filter-smoother, suitable for off-line as well as on-line state estimation for given noise and system parameters. The second level problem is split up into two, one for modifying the noise statistics and the other for modifying the system parameters. An adaptive relaxation technique is proposed for modifying the noise statistics and a modified Gauss-Newton technique is used to adjust the system parameters.

PLA folding algorithm from compatibility relations

The letter reports an algorithm for the folding of programmable logic arrays. The algorithm is valid for both column and row folding, although it has been presented considering only the simple column folding. The pairwise compatibility relations among all the pairs of the columns of the PLA are plotted in a matrix called the compatibility matrix of the PLA. A foldable compatibility matrix (FCM), a new concept defined in the letter, is then derived from the compatibility matrix. Once an FCM is obtained, the ordered pairs of fold-able columns and the reordering of the rows are readily determined

Design and flight testing of a bio-inspired plume tracking algorithm for unmanned serial vehicles

There is an increased interest on the use of UAVs for environmental research such as tracking bush fires, volcanic eruptions, chemical accidents or pollution sources. The aim of this paper is to describe the theory and results of a bio-inspired plume tracking algorithm. A method for generating sparse plumes in a virtual environment was also developed. Results indicated the ability of the algorithms to track plumes in 2D and 3D. The system has been tested with hardware in the loop (HIL) simulations and in flight using a CO2 gas sensor mounted to a multi-rotor UAV. The UAV is controlled by the plume tracking algorithm running on the ground control station (GCS).

Divide-and-Correct Algorithm for Division in a Negative Base

A divide-and-correct algorithm is described for multiple-precision division in the negative base number system. In this algorithm an initial quotient estimate is obtained from suitable segmented operands; this is then corrected by simple rules to arrive at the true quotient.

Divide-and-Correct Algorithm for Division in a Negative Base

A divide-and-correct algorithm is described for multiple-precision division in the negative base number system. In this algorithm an initial quotient estimate is obtained from suitable segmented operands; this is then corrected by simple rules to arrive at the true quotient.

An algebraic algorithm for the design and analysis of linear dynamical systems

In an earlier paper [1], it has been shown that velocity ratio, defined with reference to the analogous circuit, is a basic parameter in the complete analysis of a linear one-dimensional dynamical system. In this paper it is shown that the terms constituting velocity ratio can be readily determined by means of an algebraic algorithm developed from a heuristic study of the process of transfer matrix multiplication. The algorithm permits the set of most significant terms at a particular frequency of interest to be identified from a knowledge of the relative magnitudes of the impedances of the constituent elements of a proposed configuration. This feature makes the algorithm a potential tool in a first approach to a rational design of a complex dynamical filter. This algorithm is particularly suited for the desk analysis of a medium size system with lumped as well as distributed elements.

Deterministic Division Algorithm in a Negative Base

Described here is a deterministic division algorithm in a negative-base number system; here, the divisor is mapped into a suitable range by premultiplication, so that the choice of the quotient digit is deterministic.

Problems and Algorithms for Sequence Segmentations

The analysis of sequential data is required in many diverse areas such as telecommunications, stock market analysis, and bioinformatics. A basic problem related to the analysis of sequential data is the sequence segmentation problem. A sequence segmentation is a partition of the sequence into a number of non-overlapping segments that cover all data points, such that each segment is as homogeneous as possible. This problem can be solved optimally using a standard dynamic programming algorithm. In the first part of the thesis, we present a new approximation algorithm for the sequence segmentation problem. This algorithm has smaller running time than the optimal dynamic programming algorithm, while it has bounded approximation ratio. The basic idea is to divide the input sequence into subsequences, solve the problem optimally in each subsequence, and then appropriately combine the solutions to the subproblems into one final solution. In the second part of the thesis, we study alternative segmentation models that are devised to better fit the data. More specifically, we focus on clustered segmentations and segmentations with rearrangements. While in the standard segmentation of a multidimensional sequence all dimensions share the same segment boundaries, in a clustered segmentation the multidimensional sequence is segmented in such a way that dimensions are allowed to form clusters. Each cluster of dimensions is then segmented separately. We formally define the problem of clustered segmentations and we experimentally show that segmenting sequences using this segmentation model, leads to solutions with smaller error for the same model cost. Segmentation with rearrangements is a novel variation to the segmentation problem: in addition to partitioning the sequence we also seek to apply a limited amount of reordering, so that the overall representation error is minimized. We formulate the problem of segmentation with rearrangements and we show that it is an NP-hard problem to solve or even to approximate. We devise effective algorithms for the proposed problem, combining ideas from dynamic programming and outlier detection algorithms in sequences. In the final part of the thesis, we discuss the problem of aggregating results of segmentation algorithms on the same set of data points. In this case, we are interested in producing a partitioning of the data that agrees as much as possible with the input partitions. We show that this problem can be solved optimally in polynomial time using dynamic programming. Furthermore, we show that not all data points are candidates for segment boundaries in the optimal solution.

Optimisation Problems in Wireless Sensor Networks : Local Algorithms and Local Graphs

This thesis studies optimisation problems related to modern large-scale distributed systems, such as wireless sensor networks and wireless ad-hoc networks. The concrete tasks that we use as motivating examples are the following: (i) maximising the lifetime of a battery-powered wireless sensor network, (ii) maximising the capacity of a wireless communication network, and (iii) minimising the number of sensors in a surveillance application. A sensor node consumes energy both when it is transmitting or forwarding data, and when it is performing measurements. Hence task (i), lifetime maximisation, can be approached from two different perspectives. First, we can seek for optimal data flows that make the most out of the energy resources available in the network; such optimisation problems are examples of so-called max-min linear programs. Second, we can conserve energy by putting redundant sensors into sleep mode; we arrive at the sleep scheduling problem, in which the objective is to find an optimal schedule that determines when each sensor node is asleep and when it is awake. In a wireless network simultaneous radio transmissions may interfere with each other. Task (ii), capacity maximisation, therefore gives rise to another scheduling problem, the activity scheduling problem, in which the objective is to find a minimum-length conflict-free schedule that satisfies the data transmission requirements of all wireless communication links. Task (iii), minimising the number of sensors, is related to the classical graph problem of finding a minimum dominating set. However, if we are not only interested in detecting an intruder but also locating the intruder, it is not sufficient to solve the dominating set problem; formulations such as minimum-size identifying codes and locating dominating codes are more appropriate. This thesis presents approximation algorithms for each of these optimisation problems, i.e., for max-min linear programs, sleep scheduling, activity scheduling, identifying codes, and locating dominating codes. Two complementary approaches are taken. The main focus is on local algorithms, which are constant-time distributed algorithms. The contributions include local approximation algorithms for max-min linear programs, sleep scheduling, and activity scheduling. In the case of max-min linear programs, tight upper and lower bounds are proved for the best possible approximation ratio that can be achieved by any local algorithm. The second approach is the study of centralised polynomial-time algorithms in local graphs these are geometric graphs whose structure exhibits spatial locality. Among other contributions, it is shown that while identifying codes and locating dominating codes are hard to approximate in general graphs, they admit a polynomial-time approximation scheme in local graphs.