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Recursion is one of the most difficult programming topics for students. In this paper, an instructional method is proposed to enhance students' understanding of recursion tracing. The proposal is based on the use of rules to translate linear recursion algorithms into equivalent, iterative ones. The paper has two main contributions: the instructional method itself, and its evaluation, which is based on previous works of other authors on mental models of recursion. As a result, an enhancement was measured in the viability of mental models exhibited by students (both for linear and multiple recursion), but no significant improvement was detected in their skills for designing recursive algorithms. Evidence was also obtained of the fact that many students with (relatively) viable mental models for linear recursion have unviable mental models for multiple recursion. Finally, it was noticed that many students adopt inaccurate mental models if those models are adequate to handle the given algorithm. [ABSTRACT FROM PUBLISHER]

The proposed chord-fractal pattern has a significant impact on IC capacitor, increasing the capacitance within a limited chip area. To reduce the device area, this paper presents a modified fractal algorithm. This proposed algorithm uses various initiators to perform chord iteration on the unit cell. The iteration procedure automatically generates an area-saving fractal layout of IC capacitor. To verify the proposed algorithm, an area-saving device of chord-fractal is fabricated using UMC 0.18- \mu \textm CMOS technology. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the semi-analytical solution of Kaup-Kupershmidt equations with the help of a modified method known as the new iteration transformation technique. This method combines the Yang transform and the new iteration technique. The nonlinear terms can be calculated straightforwardly by a new iteration method. The numerical simulation results have been presented to demonstrate the reliability and validity of the proposed approach. The result confirms that the suggested technique is the best tool for dealing with any nonlinear problems arising in technology and science. In addition, in terms of figures for varying fractional order, the physical behavior of new iteration transformation technique solutions has been shown and the numerical simulation is also exhibited. The solutions of the new iteration transformation technique reveal that the projected technique is reliable, competitive and powerful for studying complex nonlinear fractional type models. [ABSTRACT FROM AUTHOR]

Many real-life problems using mathematical modeling can be reduced to scalar and system of nonlinear equations. In this paper, we develop a family of three-step sixth-order method for solving nonlinear equations by employing weight functions in the second and third step of the scheme. Furthermore, we extend this family to the multidimensional case preserving the same order of convergence. Moreover, we have made numerical comparisons with the efficient methods of this domain to verify the suitability of our method. [ABSTRACT FROM AUTHOR]

This paper develops a generalized admittance matrix approach in Fortescue coordinate system to solve unbalanced/unsymmetrical distribution networks including different number of phases. This generalized Fortescue \pi equivalent is defined in this paper for solving the heterogeneous phase, and thus Fortescue, network model. The performance of the approach is demonstrated in different model networks with number of nodes ranging between 168 and 14200. It is found that the current iteration method exploiting the decoupling in admittance matrix in Fortescue coordinate is substantially faster than the typical unbalanced three-phase solution in phase domain. The method has a significant potential for application in real time active power network management. [ABSTRACT FROM PUBLISHER]

A new compact microwave amplifier structure using an iterative technique based on the wave concept iterative procedure (WCIP) is presented. This new multilayer structure is composed of five planar interfaces of strip lines. The technique used to model this structure provides a mixed resolution in modal and spatial domain. By taking the best advantage of each resolution domain, a lower computing time is obtained. The purpose of this paper is to demonstrate that a near field amplification technique is achievable and the WCIP is suitable to electromagnetic analysis of this kind of structure. The numerical results show 13.4 dB gain at 5.6 GHz. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new four-dimensional hyperchaotic system derived from the chaotic maps of Peter de Jong's simple attractor and the discrete iterative function. In this work, our main motivation is to explore a link that can be developed to generate hyperchaos from 2D chaotic system. An association between 2D system and a higher order one was not studied in the previous literature. In fact, in the literature, there is no two-dimensional systems from which we are able to associate a four-dimensional one. In this context, a special interest is reserved to Peter de Jong system due to its exceptional advantages such as hypersensitivity and velocity. The challenge in this paper is the development of a four-dimensional hyperchaotic system associated to the Peter de Jong one while conserving its important characteristics such as hypersensitivity, velocity and the lack of equilibrium. The system structure that we will detail is different from other hyperchaotic systems widely suggested in the literature. In fact, the proposed attractor does not display any equilibrium point. A mathematical study is carried out in order to obtain time plots, Lyapunov exponents spectrum and bifurcation diagram. Finally, we will prove the high sensitivity of this system relative to its initial condition by simulations and experimental observations. [ABSTRACT FROM AUTHOR]

As part of the day-ahead market clearing process, MISO solves one of the most challenging Security Constrained Unit Commitment (SCUC) models. With footprint expansions and increased activity from financial traders, the day-ahead market unit commitment encounters significant performance challenges from time to time. This paper reviews MISO's day-ahead market clearing process and identifies the factors contributing to these performance challenges. It then shares techniques that have been developed to overcome these challenges. Three alternative backup solving approaches were developed. An incremental solving algorithm is proposed to better handle the iterative market clearing process and to perform solution polishing and commitment reason identification. Numerical results based on MISO data are presented. [ABSTRACT FROM PUBLISHER]

This paper suggests a data envelopment analysis (DEA) model for selecting the most efficient alternative in advanced manufacturing technology in the presence of both cardinal and ordinal data. The paper explains the problem of using an iterative method for finding the most efficient alternative and proposes a new DEA model without the need of solving a series of LPs. A numerical example illustrates the model, and an application in technology selection with multi-inputs/multi-outputs shows the usefulness of the proposed approach. [ABSTRACT FROM AUTHOR]

Copula models are becoming increasingly popular in engineering and financial applications. They provide a flexible way of constructing joint distributions with arbitrary one-dimensional margins and a wide variety of dependence structures. This paper studies different types of conditionalization of copula-based models. We conditionalize these models in the usual way on point values but also propose a different type of conditionalization on a new margin. This new type of conditionalization is motivated by experience with a model built for application in modeling risk in civil aviation. Changing one margin in a copula model is very easy; however, it is not equivalent to conditionalizing on a new margin. For this purpose, the technique presented by Holland and Wang [Holland PW, Wang YJ (1987) Dependence function for continuous bivariate densities. Commun. Statist. Theory Methods 16(3):867-876], called marginal replacement, is used. The main result of this paper allows a simplified way of conditionalizing on more than one univariate margin in a normal copula model. [ABSTRACT FROM AUTHOR]

In this paper, a variational Bayesian (VB)-based iterative algorithm for ARX models with random missing outputs is proposed. The distributions of missing outputs can be estimated in the VB-E step, and the distributions of unknown parameters can be estimated in the VB-M step by the estimated missing outputs and the available outputs. Compared with the expectation-maximization-based iterative algorithm, this algorithm computes the latent variable and the parameter distributions at each iteration. Therefore, it is more accurate. The simulation results demonstrate the advantages of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper we propose a modified Elliptic Net algorithm to compute pairings. By reducing the number of the intermediate variables which should be updated in the iteration loop of the Elliptic Net algorithm, we speed up the computation of pairings. Experimental results show that the proposed method is more efficient than the original Elliptic Net algorithm on Barreto-Naehrig (BN) curves which are the best choice for implementing pairings at 128-bit security level. [ABSTRACT FROM PUBLISHER]

The first aim of this paper is to give emphasis to the importance of assessing phase information when reconstructing and mapping a sound field. In fact, in acoustic analysis phase distribution is frequently simply either not considered or ignored, even though it can supply very useful information for the understanding of the mapping itself or for further analyses. In this paper a procedure to carry out phase mapping of acoustic sources in beamforming measurement is illustrated. The second aim of this paper is to propose a straightforward iterative optimization algorithm based on the monopole substitution starting from beamforming results. It allows for the reconstruction of sound field without the use of any matrix inversion. Both numerical and experimental validations of the method are presented. Results shown hereafter prove the effectiveness of the approach. [ABSTRACT FROM AUTHOR]

This paper examines the allocation of yard cranes and blocks for yard activities in container terminals. In this paper, the yard cranes are confined to rail mounted gantry cranes (RMGC), which are characterized by the restricted traveling range on a pair of rails. Since RMGCs and yard blocks are tightly bound to each other, when allocating them, we should make sure that the RMGCs allocated for a yard activity are able to together cover the blocks allocated for the corresponding yard activity. In addition, considering that there are four basic activities occurring in the yard which compete with each other for the scarce resources and have different requirements and priorities in the allocation of blocks and yard cranes, we treat them in a single model rather than in multiple independent models as were generally done in literature. A mixed integer programming model is constructed, and an iterative decomposition solution procedure is proposed for the problem. Based on the solution procedure, a decision support system is developed and implemented for a terminal in Tianjin seaport. Using the actual data, the numerical experiments show the effectiveness and efficiency of the decision support system. [ABSTRACT FROM AUTHOR]

This paper presents a new triaxial accelerometer calibration method using a mathematical model of six calibration parameters: three gain factors and three biases. The fundamental principle of the proposed calibration method is that the sum of the triaxial accelerometer outputs is equal to the gravity vector when the accelerometer is stationary. The proposed method requires the triaxial accelerometer to be placed in six different tilt angles to estimate the six calibration parameters. Since the mathematical model of the calibration parameters is nonlinear, an iterative method is used. The results are verified via simulations by comparing the estimated gain factors and biases with the true gain factors and biases. The simulation results confirm that the proposed method is applicable in extreme cases where the gain factor is 1000 V/(m/s²) and the bias is ±100 V, as well as the cases where the gain factor is 0.001 V/(m/s²) and the bias is 0 V. The proposed calibration method is also experimentally tested with two different triaxial accelerometers, and the results are validated using a mechanical inclinometer. The experimental results show that the proposed method can accurately estimate gain factors and biases even when the initial guesses are not close to the true values. In addition, the proposed method has a low computational cost because the calculation is simple, and the iterative method usually converges within three iteration steps. The error sources of the experiments are discussed in this paper. [ABSTRACT FROM AUTHOR]

This paper provides simple lower bounds on the number of iterations which is required for successful message-passing decoding of some important families of graph-based code ensembles (including low-density parity-check (LDPC) codes and variations of repeat-accumulate codes). The transmission of the code ensembles is assumed to take place over a binary erasure channel, and the bounds refer to the asymptotic case where we let the block length tend to infinity. The simplicity of the bounds derived in this paper stems from the fact that they are easily evaluated and are expressed in terms of some basic parameters of the ensemble which include the fraction of degree-2 variable nodes, the target bit erasure probability, and the gap between the channel capacity and the design rate of the ensemble. This paper demonstrates that the number of iterations which is required for successful message-passing decoding scales at least like the inverse of the gap (in rate) to capacity, provided that the fraction of degree-2 variable nodes of these turbo-like ensembles does not vanish (hence, the number of iterations becomes unbounded as the gap to capacity vanishes). [ABSTRACT FROM AUTHOR]

This paper considers the maximization of information rates for the Gaussian frequency-selective interference channel, subject to power and spectral mask constraints on each link. To derive decentralized solutions that do not require any cooperation among the users, the optimization problem is formulated as a static noncooperative game of complete information. To achieve the so-called Nash equilibria of the game, we propose a new distributed algorithm called asynchronous iterative water-filling algorithm. In this algorithm, the users update their power spectral density (PSD) in a completely distributed and asynchronous way: some users may update their power allocation more frequently than others and they may even use outdated measurements of the received interference. The proposed algorithm represents a unified framework that encompasses and generalizes all known iterative water-filling algorithms, e.g., sequential and simultaneous versions. The main result of the paper consists of a unified set of conditions that guarantee the global converge of the proposed algorithm to the (unique) Nash equilibrium of the game. [ABSTRACT FROM AUTHOR]

The analysis of medical images requires image segmentation to distinguish the boundaries of irregular regions such as tumors in images. However, segmentation of medical images with intensity inhomogeneity has always been a challenging task in image processing. In this paper, we have proposed a new model for segmentation of medical image having inhomogeneous intensities. In the proposed model, we have used hybrid image data obtained from the product of given image with smooth image and difference of smooth product image from product image. The model uses both local and global information of the image. The proposed model outperforms the existing models qualitatively and quantitatively i.e. in terms of number of iterations and CPU time. For the solution of proposed model we have used some of the numerical schemes such as Explicit and Semi-Implicit schemes. The model is further tested for different type of real medical images. The results showed that the proposed model also performs well in images having intensity inhomogeneity and blurred edges as well. [ABSTRACT FROM AUTHOR]

In this paper, we establish an iterative algorithm and estimation of solutions for a fractional turbulent flow model in a porous medium under a suitable growth condition. Our main tool is the monotone iterative technique. [ABSTRACT FROM AUTHOR]

This paper focuses on the use of quadratic time-frequency distributions (QTFDs) to characterize the temporal variation of low-frequency electromechanical oscillations (LFEOs) using ringdown data. A refined Margenau-Hill distribution (MHD) and a procedure to extract the instantaneous frequencies and damping factors as well as initial phase angles of system low-frequency modes when the analyzed signal is multi-component are proposed. The refinement process enjoys a fast-converging iterative algorithm and without loss of generality it can be applied to other QTFDs for using in other applications. A non-stationary synthetic signal as well as simulated ringdown data of a 5-area, 16-machine power system and real measured data of Western Systems Coordinating Council (WSCC) system are used to demonstrate the efficiency of the proposed method in the presence of measurement noise. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to introduce and consider a new hybrid shrinking projection method for finding a common element of the set EP of solutions of a generalized equilibrium problem, the common fixed point set F of finite uniformly closed families of countable Bregman quasi-Lipschitz mappings in reflexive Banach spaces. It is proved that under appropriate conditions, the sequence generated by the hybrid shrinking projection method converges strongly to some point in $\mathit{EP} \cap F$. Relative examples are given. Strong convergence theorems are proved. The application for Bregman asymptotically quasi-nonexpansive mappings is also given. The main innovative points in this paper are as follows: (1) the notion of the uniformly closed family of countable Bregman quasi-Lipschitz mappings is presented and the useful conclusions are given; (2) the relative examples of the uniformly closed family of countable Bregman quasi-Lipschitz mappings are given in classical Banach spaces $l^{2}$ and $L^{2}$; (3) the application for Bregman asymptotically quasi-nonexpansive mappings is also given; (4) because the main theorems do not need the boundedness of the domain of mappings, so a corresponding technique for the proof is given. This new results improve and extend the previously known ones in the literature. [ABSTRACT FROM AUTHOR]

The assessment of pavement cracks is one of the essential tasks for road maintenance. This paper presents a novel framework, called ITVCrack, for automated crack extraction based on iterative tensor voting (ITV), from high-density point clouds collected by a mobile laser scanning system. The proposed ITVCrack comprises the following: 1) the preprocessing involving the separation of road points from nonroad points using vehicle trajectory data; 2) the generation of the georeferenced feature (GRF) image from the road points; and 3) the ITV-based crack extraction from the noisy GRF image, followed by an accurate delineation of the curvilinear cracks. Qualitatively, the method is applicable for pavement cracks with low contrast, low signal-to-noise ratio, and bad continuity. Besides the application to GRF images, the proposed framework demonstrates much better crack extraction performance when quantitatively compared to existing methods on synthetic data and pavement images. [ABSTRACT FROM PUBLISHER]

Networks based on IEEE 802.11 standard are one of the main options for deployment in industrial environment. Degradation of throughput in congested networks and short-term unfairness are well-known drawbacks of 802.11 DCF and similar MAC protocols. Those shortcomings represent significant limitation in forecasted growth of wireless usage. This is especially important in industrial wireless networks (IWN) where the scalability of wireless MAC is one of the main requirements. In this paper, a novel self-adapting MAC protocol (SaMAC) is defined and mathematically modeled. SaMAC employs constrained countdown freezing enhanced with shifted window mechanism. As a result, the protocol outperforms 802.11 DCF standard as well as shifted contention window (SCW) and constrained countdown freezing (CPCF) protocols in achieved throughput, fairness, and jitter, while keeping simple implementation. Despite protocol’s simple design, it is shown that its mathematical model is extremely complex. For proposed protocol, the assumption of constant contention loss probability, which is normally used for modeling of MAC schemes, does not hold. In the presented multidimensional Markov chain model, a unique iterative method for determining contention loss probability is developed as well as a method for throughput calculation based on such a chain. Accuracy of the presented model is verified in several network scenarios. Considering the performance of the proposed protocol, authors believe that it could be of benefit to deploy it in heavily loaded wireless networks with timing constraints, such as IWNs. [ABSTRACT FROM AUTHOR]

Compressed sensing (CS) based radar imaging requires the use of a mathematical model of the observation process. Inaccuracies in the observation model may cause defocusing in the reconstructed images. In the observation process, the observation positions are usually not known perfectly. Imperfect knowledge of the observation positions is a major source of model errors in imaging. In this paper, a method is proposed to compensate the observation position errors in CS-based radar imaging. Instead of treating the observation-position-induced model errors as phase errors in the data, the proposed method can determine the observation position errors as part of the imaging process. It uses an iterative algorithm, which cycles through steps of target reconstruction and observation position error estimation and compensation. The proposed method can estimate the observation position errors accurately, and the reconstruction quality of the target images can be improved significantly. Simulation results and experimental results from rail-mounted radar and airborne synthetic aperture radar are presented to show the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

In this paper, an iterative algorithm is proposed to retrieve the particle-size distributions via Fraunhofer diffraction. A dual integral inversion was proposed in our previous work, the inversion is robust and generates precise particle sizing, if the diffraction pattern can be accurately captured. In real applications, the pattern can only be partially detected, and the inversion fails to reconstruct the size distributions in detail. However, the results of the inversion can be used to produce an initial estimate. Then, a simulated diffraction pattern was generated from the estimated particle sizes. The deviation between the measured pattern and the simulated one was deduced to correct the results of particle sizing. The corrections can be achieved in an iterative approach, and the particle-size distribution was updated subsequently. The iteration stopped once the deviation was below the target value. Both simulation and experiment were conducted to validate the feasibility and effectiveness of the proposed algorithm. The results demonstrate that the size distribution from the proposed algorithm agrees well with the original phantoms for both noise-free and noise-contaminated data. [ABSTRACT FROM AUTHOR]

Convergence of classical parallel iterations is detected by performing a reduction operation at each iteration in order to compute a residual error relative to a potential solution vector. To efficiently run asynchronous iterations, blocking communication requests are avoided, which makes it hard to isolate and handle any global vector. While some termination protocols were proposed for asynchronous iterations, only very few of them are based on global residual computation and guarantee effective convergence. But the most effective and efficient existing solutions feature two reduction operations, which constitutes an important factor of termination delay. In this paper, we present new, non-intrusive, protocols to compute a residual error under asynchronous iterations, requiring only one reduction operation. Various communication models show that some heuristics can even be introduced and formally evaluated. Extensive experiments with up to 5,600 processor cores confirm the practical effectiveness and efficiency of our approach. [ABSTRACT FROM AUTHOR]

The paper presents a new model of the STATCOM aimed at power flow solutions using the Newton–Raphson method. The STATCOM is made up of the series connection of a voltage-source converter (VSC) and its connecting transformer. The VSC is represented in this paper by a complex tap-changing transformer whose primary and secondary windings correspond, notionally speaking, to the VSC's ac and dc buses, respectively. The magnitude and phase angle of the complex tap changer are said to be the amplitude modulation index and the phase shift that would exist in a PWM inverter to enable either reactive power generation or absorption purely by electronic processing of the voltage and current waveforms within the VSC. The new STATCOM model allows for a comprehensive representation of its ac and dc circuits—this is in contrast to current practice where the STATCOM is represented by an equivalent variable voltage source, which is not amenable to a proper representation of the STATCOM's dc circuit. One key characteristic of the new VSC model is that no special provisions within a conventional ac power flow solution algorithm is required to represent the dc circuit, since the complex tap-changing transformer of the VSC gives rise to the customary ac circuit and a notional dc circuit. The latter includes the dc capacitor, which in steady-state draws no current, and a current-dependent conductance to represent switching losses. The ensuing STATCOM model possesses unparalleled control capabilities in the operational parameters of both the ac and dc sides of the converter. The prowess of the new STATCOM power flow model is demonstrated by numerical examples where the quadratic convergence characteristics of the Newton–Raphson method are preserved. [ABSTRACT FROM PUBLISHER]

In this paper, a new iterative algorithm for the analysis of properties of magnetic shielding systems is proposed. Since such shielding systems for low frequency applications are composed of thin-walled shells with magnetic materials of high permeability, the thin shell approximation is adopted and a numerical integral formulation of the ensuing magnetostatic problem is obtained in the form of a convolution equation. This algebraic system is eventually solved iteratively by exploiting the convolution properties of the discrete Fourier transform. The convergence properties of the procedure are analyzed and tested on two case studies where isotropic and anisotropic magnetic shields are used. [ABSTRACT FROM AUTHOR]

Cloud computing economically enables customers with limited computational resources to outsource large-scale computations to the cloud. However, how to protect customers' confidential data involved in the computations then becomes a major security concern. In this paper, we present a secure outsourcing mechanism for solving large-scale systems of linear equations (LE) in cloud. Because applying traditional approaches like Gaussian elimination or LU decomposition (aka. direct method) to such large-scale LEs would be prohibitively expensive, we build the secure LE outsourcing mechanism via a completely different approach—iterative method, which is much easier to implement in practice and only demands relatively simpler matrix-vector operations. Specifically, our mechanism enables a customer to securely harness the cloud for iteratively finding successive approximations to the LE solution, while keeping both the sensitive input and output of the computation private. For robust cheating detection, we further explore the algebraic property of matrix-vector operations and propose an efficient result verification mechanism, which allows the customer to verify all answers received from previous iterative approximations in one batch with high probability. Thorough security analysis and prototype experiments on Amazon EC2 demonstrate the validity and practicality of our proposed design. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new channel model which introduces dependent insertion, deletion, and substitution (DIDS) errors. This channel model mimics the write channel found in bit-patterned media recording (BPMR) systems. It consists of a ternary Markov state channel and a two-state binary symmetric channel (BSC). The ternary Markov state channel produces data-dependent and paired insertion-deletion errors while the two-state BSC produces random substitution errors, as well as burst-like substitution errors in the vicinity of insertions and deletions. In addition, we modify the inner decoder of the Davey-MacKay (DM) coding scheme for the proposed channel model. For the case where there are no burst-like substitution errors, computer simulations show that our modified inner decoder (which takes into account the dependencies between synchronization errors) yields superior frame error rate (FER) performance compared to that when the symbol-level inner decoder by Briffa (which ignores the dependencies between synchronization errors) is used. As the (computational) complexity of our inner decoder increases with the length of the burst-like substitution errors, we further propose a reduced-complexity variant of our inner decoder to handle these errors. Computer simulations show that under iterative decoding, FERs below 10^-5 can be achieved with the reduced-complexity variant and a code of rate 0.71, when the insertion/deletion rates are low (\leq 10^-3) and the burst-like error lengths before and after a synchronization error are short (\leq 5). [ABSTRACT FROM AUTHOR]

In performance modeling of parallel synchronous iterative applications, the longest individual execution time among parallel processors determines the iteration time and often must be estimated for performance analysis. This involves the mean maximum calculation which has been a challenge in computer modeling for a long time. For large systems, numerical methods are not suitable because of heavy computation requirements and inaccuracy caused by rounding. On the other hand, previous approximation methods face challenges of accuracy and generality, especially for heterogeneous computing environments. This paper presents an interesting property of extreme values to enable Effective Mean Maximum Approximation (EMMA). Compared to previous mean maximum execution time approximation methods, this method is more accurate and general to different computational environments. [ABSTRACT FROM AUTHOR]

In this paper, we present a probabilistic spatial approach to build compact 3-D representations of unknown objects probed by tactile sensors. Our approach exploits the high frame rates provided by modern tactile sensors and utilizes Kalman filters to build a probabilistic model of the contact point cloud that is efficiently stored in a kd-tree. The quality of generated shape representations is compared with a naive averaging approach, and we show that our method provides superior accuracy. We also evaluate the feasibility of object classification combining the generated object representations, together with the iterative closest point algorithm. [ABSTRACT FROM AUTHOR]

Optimal reactive power flow applications often model large numbers of discrete shunt devices as continuous variables, which are rounded to their nearest discrete value at the final iteration. This can degrade optimality. This paper presents novel methods based on probabilistic and adaptive threshold approaches that can extend existing security constrained optimal reactive power flow methods to effectively solve large-scale network problems involving discrete shunt devices. Loss reduction solutions from the proposed techniques were compared to solutions from the mixed integer nonlinear mathematical programming algorithm (MINLP) using modified IEEE standard networks up to 118 buses. The proposed techniques were also applied to practical large-scale network models of Great Britain. The results show that the proposed techniques can achieve improved loss minimization solutions when compared to the standard rounding method. [ABSTRACT FROM AUTHOR]

Abstract  This paper is concerned with a diffusive vector disease model with distributed delay. The existence of travelling wave front solutions connecting the zero equilibrium and the positive equilibrium is established by using an iterative technique and a nonstandard ordering for the set of profiles of the corresponding wave system recently developed by Wang, Li and Ruan (Travelling wave fronts in reactiondiffusion systems with spatio-temporal delays. J. Differential Equations 222 (2006), 185–232). The existence of travelling front solutions shows that there is a moving zone of transition from the disease free state to the infective state. [ABSTRACT FROM AUTHOR]

This paper considers the performance, on the binary erasure channel, of low-density parity-check (LDPC) codes without repeated edges in their Tanner graphs. A modification to existing finite-length analysis algorithms is presented for these codes. [ABSTRACT FROM AUTHOR]

This paper presents a new extraction method for effective channel length (Leff) and source/drain series resistance (RSD) in ultrashort-channel MOSFETs using an iterative process, which is a modified channel resistance method (CRM). Although conventional methods for extracting Leff and RSD, such as the channel resistance and shift-and-ratio methods, are considered to be the most consistent techniques, they are not valid for shorter channel transistors, such as the total resistance (Rtot = VDS/IDS) of MOSFETs, and do not scale proportionately with poly-gate length (Lpoly). This error results from the fact that these methods assume the effective mobility (μeff) of long- and short-channel transistors to be the same. This assumption inevitably lowers the accuracy of the extracted channel length in ultrashort-channel MOSFETs. Therefore, an improved CRM using an iterative procedure has been proposed. This iteration method takes into account the fact that mobility is degraded in shorter channel devices. By compensating for the mobility in long-channel devices, more accurate approximations for Leff and RSD are extracted compared to conventional methods. [ABSTRACT FROM AUTHOR]

System identification involves identification of a behavioral model that best explains the measured behavior of a structure. This research uses a strategy of generation and iterative filtering of multiple candidate models for system identification. The task of model filtering is supported by measurement-interpretation cycles. During each cycle, the location for subsequent measurement is chosen using the predictions of current candidate models. In this paper, data mining techniques are proposed to support such measurement-interpretation cycles. Candidate models, representing possible states of a structure, are clustered using a technique that combines principal component analysis and K-means clustering. Representative models of each cluster are used to place sensors for subsequent measurement on the basis of the entropy of their predictions. Results show that clustering is necessary to identify the different groups of candidate models. The entropy of predictions is found to be a valid stopping criterion for iterative sensor addition. Clustering helps classify models and, thus, it provides useful support to engineers for further decision making. [ABSTRACT FROM AUTHOR]

The problem of computing functions of values at the nodes in a network in a fully distributed manner, where nodes do not have unique identities and make decisions based only on local information, has applications in sensor, peer-to-peer, and ad hoc networks. The task of computing separable functions, which can be written as linear combinations of functions of individual variables, is studied in this context. Known iterative algorithms for averaging can be used to compute the normalized values of such functions, but these algorithms do not extend, in general, to the computation of the actual values of separable functions. The main contribution of this paper is the design of a distributed randomized algorithm for computing separable functions. The running time of the algorithm is shown to depend on the running time of a minimum computation algorithm used as a subroutine. Using a randomized gossip mechanism for minimum computation as the sub-routine yields a complete fully distributed algorithm for computing separable functions. For a class of graphs with small spectral gap, such as grid graphs, the time used by the algorithm to compute averages is of a smaller order than the time required by a known iterative averaging scheme. [ABSTRACT FROM AUTHOR]

The article proposes and analyzes an age-structured prey-predator model with delays. It analyzes mathematical analyses of the model equations with regard to boundedness of solutions, permanence, and stability. The sufficient conditions for the permanence of the system are obtained by using the persistence theory for infinite-dimensional systems. This paper constructs suitable Lyapunov functions and uses an iterative technique in order to obtain sufficient conditions for the global asymptotic stability of the positive equilibrium of the model.

The Iterative Closest Point (ICP) algorithm is one of the most widely used methods for point-set registration. However, being based on local iterative optimization, ICP is known to be susceptible to local minima. Its performance critically relies on the quality of the initialization and only local optimality is guaranteed. This paper presents the first globally optimal algorithm, named Go-ICP, for Euclidean (rigid) registration of two 3D point-sets under the $L_2$ error metric defined in ICP. The Go-ICP method is based on a branch-and-bound scheme that searches the entire 3D motion space $SE(3)$ . By exploiting the special structure of $SE(3)$ geometry, we derive novel upper and lower bounds for the registration error function. Local ICP is integrated into the BnB scheme, which speeds up the new method while guaranteeing global optimality. We also discuss extensions, addressing the issue of outlier robustness. The evaluation demonstrates that the proposed method is able to produce reliable registration results regardless of the initialization. Go-ICP can be applied in scenarios where an optimal solution is desirable or where a good initialization is not always available. [ABSTRACT FROM PUBLISHER]

This paper describes iterative methods for the high frequency electromagnetic analysis using the finite element method of Maxwell equations including displacement current. The conjugate orthogonal conjugate gradient method has been widely used to solve a complex symmetric system. However, the conventional method suffers from oscillating convergence histories in large-scale analysis. In this paper, to solve large-scale complex symmetric systems arising from the formulation of the E method, an iterative substructuring method like the minimal residual method is presented, and the performance of the convergence of the method is evaluated by numerical results. As the result, the proposed method shows a stable convergence behavior and a fast convergence rate compared to other iterative methods. [ABSTRACT FROM AUTHOR]

This paper considers the maximization of certain equivalent reward generated by a Markov decision process with constant risk sensitivity. First, value iteration is used to optimize possibly time-varying processes of finite duration. Then a policy iteration procedure is developed to find the stationary policy with highest certain equivalent gain for the infinite duration case. A simple example demonstrates both procedures. [ABSTRACT FROM AUTHOR]

The topology of the Generalized Transportation Problem, at the end of each iteration of the stepping-stone method, is characterized by a variable number of loops to which are attached multiple branched side chains or trees. An efficient computer representation of this structure and methods for updating it are described in this paper. [ABSTRACT FROM AUTHOR]

A stage-structured predator-prey model (stage structure for both predator and prey) with modified Leslie-Gower and Holling-II schemes is studied in this paper. Using the iterative technique method and the fluctuation lemma, sufficient conditions which guarantee the global stability of the positive equilibrium and boundary equilibrium are obtained. Our results indicate that for a stage-structured predator-prey community, both the stage structure and the death rate of the mature species are the important factors that lead to the permanence or extinction of the system. [ABSTRACT FROM AUTHOR]

Iterative localization algorithms are critical part in the control of mobile autonomous robots because they feed fundamental position information to the robots. In a harsh unknown environment, the estimation of environmental noise is hardly obtained during the movement of the robots. It means that the state-of-the-art methods, which increase localization accuracy using error management, are unsuitable. In this paper, we deduced an upper bound of the localization error without knowing the precise model of environment noise when the anchor nodes have position errors. Utilizing the minimum upper bound, we can construct an optimal localization linear system of iterative localization algorithms based on least square. An algorithm of generating localization linear system is proposed by using the minimum upper bound. The algorithm reduces the impact of the shortage of environmental information on localization error propagation. Our simulation results show that the algorithm is insensitive to noise and can improve the localization accuracy by constructing a proper localization linear system with a high probability. [ABSTRACT FROM AUTHOR]

The paper deals with modelling of nonlinear transient responses that occur in the technical and natural objects. In the field of non-linear phenomena are generated structures that have regular and chaotic nature. As a modelling tool, we used a modification of the logistic equation. Search and display of various structures was achieved when using parameter iterations of modified logistic equation. An iterative method in this case appears to be a very effective tool. The novelty of the method is in creating regular and chaotic structures in the time development of nonlinear functions. [ABSTRACT FROM AUTHOR]

This paper deals with scrutinizing the convergence properties of iterative methods to solve linear system of equations. Recently, several types of the preconditioners have been applied for ameliorating the rate of convergence of the Accelerated Overrelaxation (AOR) method. In this paper, we study the applicability of a general class of the preconditioned iterative methods under certain conditions. More precisely, it is demonstrated that the preconditioned Mixed-Type Splitting (MTS) iterative methods can surpass the preconditioned AOR iterative methods for an entirely general class of preconditioners handled by Wang and Song [J. Comput. Appl. Math. 226 (2009), no. 1, 114-124]. Finally some numerical results are elaborated which confirm the validity of the established results. [ABSTRACT FROM AUTHOR]

This paper provides a new exact iterative method for the following problem. Two decision makers, a leader and a follower, compete to attract customers from a given market. The leader opens $$p$$ facilities, anticipating that the follower will react to the decision by opening $$r$$ facilities. Each customer patronizes the closest opened facility. The goal is to find $$p$$ facilities for the leader to maximize his market share. It is known that this problem is $$\Sigma ^P_2$$ -hard and can be presented as an integer linear program with a large number of constraints. Based on this representation, we design the new iterative exact method. A local search algorithm is used at each iteration to find a feasible solution for a system of constraints. Computational results and comparison with other exact methods show that the new method can be considered as one of the alternative approaches among the most advanced exact methods for the problem. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to study a viscosity iterative algorithm for finding a common element of the set of solutions of a general variational inequality problem for two inverse strongly accretive operators and the set of fixed points of a δ-strict pseudocontraction in a real q-uniformly smooth Banach space. Some strong convergence theorems are obtained under appropriate conditions. As an application, we prove some strong convergence theorems for fixed point problems and variational inequality problems or equilibrium problems in Hilbert spaces. These results improve and extend the corresponding results announced by many others. [ABSTRACT FROM AUTHOR]

Making predictions about environmental systems is a challenge due to the high level of uncertainty involved. In this paper we give a general formulation of prediction under uncertainty as a boundary problem. This leads to development of a methodology for making predictions under uncertainty, named Iterative Closed Question Modelling (ICQM). ICQM involves iteratively devising questions and testing the certainty of their answers by creating complete model scenarios (complete taken to include structure, parameters and inputs for each scenario instance). The model scenarios are categorised in terms of which answer they support, and whether they are plausible or not. Using a simple two-parameter flow duration curve model, the paper demonstrates the application of ICQM using eight alternative uncertainty analysis techniques. ICQM provides a useful and generic approach to making predictions under uncertainty, helps to understand how existing techniques address the boundary problem differently and promotes the development of new techniques. [ABSTRACT FROM AUTHOR]