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This paper presents a generalized algorithm to eliminate spikes of common-mode voltages (CMV) caused by dead-time effect for common-mode voltage reduction pulse width modulation (CMVRPWM). The characteristics of the CMV spikes for the popular CMVRPWM strategies (AZSPWM1, NSPWM, CRLO-CMVRPWM, and SLO-CMVRPWM) are studied and compared by analyzing the extreme switch pulse patterns. The proposed CMV spikes elimination method directly adjusts the injected zero-sequence voltages instead of the durations of the adopted voltage space vectors to avoid the overlaps of the adjacent dead time periods. The CMV spikes can be eliminated regardless of the output voltages in the dead time periods; thus, the signs of phase currents are not needed to detect and overcome the problem caused by the resolution of the current sensors when the phase currents approach to zero. In addition, an effective method by online selecting low or high active pulses for the three legs is proposed to ensure that at most one leg switches between adjacent carrier periods. The proposed method is generalized and effective for all the CMVRPWM with symmetrical switch pulse patterns and no simultaneous switching problem. The simulation and experimental results validate the effectiveness.

This paper presents a novel design methodology for discrete-time internal model control (IMC) used to compute a disturbance filter. The proposed method employs a generalized algorithm for disturbance rejection and for process dynamics compensation. In IMC, the controller is designed based on a model of the process, while ensuring a desired closed loop performance trajectory (for setpoint tracking). However, in some situations, for example poorly damped systems, the open loop poles of the process affect the closed loop disturbance rejection dynamics. The novel design methodology presented is able to compensate both process dynamics and input disturbances. The method is validated both in simulations and in experimental tests on a poorly damped mass–spring–damper testbench.

Optical sensors, coupled with mathematical algorithms, have proven effective at determining more accurate mid-season nitrogen (N) fertilizer recommendations in winter wheat. One parameter required in making these recommendations is in-season grain yield potential at the time of sensing. Four algorithms, with different methods for determining grain yield potential, were evaluated for effectiveness to predict final grain yield and the agronomic optimum N rate (AONR) at 34 site-years. The current N fertilizer optimization algorithm (CNFOA) outperformed the other three algorithms at predicting yield potential with no added N and yield potential with added N (R2 = 0.46 and 0.25, respectively). However, no differences were observed in the amount of variability accounted for among all four algorithms in regards to predicting the AONR. Differences were observed in that the CNFOA and proposed N fertilizer optimization algorithm (PNFOA), under predicted the AONR at approximately 75 % of the site-years; whereas, the generalized algorithm (GA) and modified generalized algorithm (MGA) recommended N rates under the AONR at about 50 % of the site-years. The PNFOA was able to determine N rate recommendations within 20 kg N ha−1 of the AONR for half of the site-years; whereas, the other three algorithms were only able recommend within 20 kg N ha−1 of the AONR for about 40 % of the site-years. Lastly, all four algorithms reported more accurate N rate recommendations compared to non-sensor based methodologies and can more precisely account for the year to year variability in grain yields due to environment.

One of the main challenges in applying optimization-based scheduling techniques in process industries stems from the different process characteristics and constraints that need to be taken into account when generating a schedule. For instance, consideration of sequence-dependent changeovers may easily make the resulting optimization model computationally expensive. Accordingly, building upon the recently proposed Discrete-Continuous Algorithm (Lee and Maravelias, 2018), we propose generalized algorithm that enables accurate and fast solution of difficult instances while efficiently handling a wide range of process characteristics. The algorithm combines modeling versatility with computational tractability while guaranteeing the feasibility and accuracy of the final solution. Through a case study inspired by a real-world brewing process, we show that our algorithm provides accurate and high quality solutions to industrial-scale instances in reasonable time.

Herein we present a generalized algorithm for processing activity images. Existing algorithms are applicable only to particular cases, and a new, broader approach is therefore proposed here that is based on a set of tuneable filters for images, using an extension of the addition and subtraction operations. The choice of tuning parameter is determined based on the desired result in each experimental case. We include several objective criteria to guide the choice of the most suitable value for the parameter. The use of our approach is exemplified with typical images with dynamic speckle, such as reading under paper, corn seeds and ultrasound images. These examples are also potentials applications in engineering environments.

Essence and role of estimation of quality of medicare are examined in the article. The evolution of this category is presented, the basic requirements, criteria and indicators of estimation of quality of medicare, are set forth. The generalized algorithm of estimation of quality of medicare, built on the basis of procedures of fuzzy logic and interval mathematics, are offered. An algorithm supposes forming of fuzzy standards with the interval membership functions. The generalized algorithm of estimation of quality of medicare supposes standard procedure of fuzzy evaluation on fuzzy conclusion according to Mamdani Algorithm or the comprehensive approach to the estimation of quality of medicare, based on the results of the expert questioning (fuzzy model with linguistic and point scales).

Imageedgedetectionprocessisoneoftheimportantprocedureofdigitalimageprocessing.Themainaimofthispaperis,todetectaparticularimagefromthebackgroundbyusingcoddedmachinelanguageandseparatetheimagewithmaximumaccuracy.Therequiredimageextractedfrombackgroundisfinallyreproduced.Theimagequalityassessmentresearchisusedtomeasurethequalityofimagesthatisusedinprocess.Duetolowimagequalityandpossiblefactors,theboundaryregionsoftheimagesmaybeunclear.Theedgedetectionprocessmakesuncertainedgedetectionpointsandresultingimproperdeterminationvaluesintheimages.ToanalyzetheperformanceofedgedetectionprocessCannyedgedetectionoperatoraretaken.

This study is a transformation of the method of a former work of the same authors for selecting the optimal fuzzy implication for inference making, into a generalized algorithm which provides with two equivalent mechanisms for the implication selection. An example involving both variations of the method is included to illustrate each process. The results obtained verify that both of the techniques produce the same outcome using the same data.

The paper presents the generalized algorithms for the identification of electrical appliances working in the household based on measurements of the aggregated current and voltage. Characteristics of the typical apartment and types of devices operating inside are provided. Detailed steps of the proposed algorithm are discussed, including the event detection and classification of particular groups of appliances. Selected features used for the device identification are introduced. Experimental results in various scenarios are presented, proving advantages of the proposed approach over methods used previously.

Analytical algorithms to compute flux distribution on central receiver are considered as a faster alternative to ray tracing. They have quite too many modifications, with HFLCAL and UNIZAR being the most recognized and verified. In this work, a generalized algorithm is presented which is valid for arbitrary sun shape of radial symmetry. Heliostat mirrors can have a nonrectangular profile, and the effects of shading and blocking, strong defocusing and astigmatism can be taken into account. The algorithm is suitable for parallel computing and can benefit from hardware acceleration of polygon texturing.

Delay differential equations (DDEs) are widely utilized as the mathematical models in engineering fields. In this paper, a method is proposed to analyze the stability characteristics of periodic DDEs with multiple time-periodic delays. Stability charts are produced for two typical examples of time-periodic DDEs about milling chatter, including the variable-spindle speed milling system with one-time-periodic delay and variable pitch cutter milling system with multiple delays. The simulations show that the results gained by the proposed method are in close agreement with those existing in the past literature. This indicates the effectiveness of our method in terms of time-periodic DDEs with multiple time-periodic delays. Moreover, for milling processes, the proposed method further provides a generalized algorithm, which possesses a good capability to predict the stability lobes for milling operations with variable pitch cutter or variable-spindle speed.

The multi-relational social network is a new social network, which is proposed in recent years and more complex than single relational social network. Therefore, the existing community discovery algorithm is lack and their results are crude. The paper proposes a new algorithm for discovering community in multi-relational social network based on modified common neighbors similarity. The core idea is the more common neighbors are shared between two nodes, the more similar the nodes are. Finally, we test our generalized algorithm on an artificial sparse network in four dimensions.

This paper proposes a novel algorithm for the skeletonization of binary and gray digital images. We are proposing an algorithm which can be easily implemented on Field Programmable Gate Arrays (FPGA).In this paper , we are proposing an algorithm for two dimensional digital image skeletonization, which can be easily extendible to three dimensional images also. No complex commutations, large set of structuring elements are used, which makes FPGA implantation efficient. Resulting skeletons for many objects are presented in the paper.

This letter presents a closed-form algorithm for estimating the three-dimensional (3-D) location (azimuth angle, elevation angle, and range) of a single source with uniform circular array (UCA). Based on a correlation, a closed-form method was recently proposed to estimate the two-dimensional (2-D) angle (azimuth and elevation angle) of a single source with UCA. This letter proposes a generalized algorithm that extends the previous work to a 3-D problem. The proposed algorithm provides all the estimation parameters simultaneously and is computationally simple. Numerical examples are also presented to demonstrate the performance of the proposed algorithm.

This paper demonstrates the need for an integrated approach to improve the accuracy of corpse age calculation based on measurements of a heterogeneous nature and conditions of partially distorted or incomplete data, using modern information intelligent technologies. A generalized algorithm developed on the basis of various mathematical methods of primary data processing and the extraction of different structures is presented, in addition to the reliability of the information.Показана актуальность разработки комплексного подхода для повышения точности вычисления возраста трупа по совокупности измерений параметров разнородного характера в условиях частично искаженных или неполных данных с использованием современных информационных интеллектуальных технологий. Представлен обобщенный алгоритм, разработанный на основании использования различных математических методов первичной обработки данных и извлечения разной по структуре и достоверности информации, который позволяет сформировать наиболее рациональную по критерию точности оценку возраста индивидуума.

The use of cloud information technologies for measurement, control, and management of distribution power grids with direct and alternating current couplings are considered. Requirements for databases for carrying out synchronous scalar direct-current measurements and synchronous vector alternating-current measurements are developed. Different scenarios of steady-state and transient regimes are examined. A generalized algorithm for the control and management of the distribution grid is proposed.

The problem of creating the mechanism of an expert system fuzzy inference meant for decision-making on the combine process adjustment is considered. The fuzzy inference algorithm is based on the domain models of ‘prior configuration’ and ‘process adjustment’. Fuzzification, composition, and defuzzification are general stages of the problem solution. The problem-solving mechanism is based on the deductive scheme (for the prior configuration problem), and on the inductive one (for the process adjustment problem). The specific feature of the proposed problem-solving algorithm is the hypothesis testing of emerging combining process non-conformances under the machine parameter variations. In this case, the validity of the exception condition generation when an additional breakdown in the technological process occurs is checked. The developed fuzzy inference algorithm and the domain model based on the fuzzy expert knowledge permit to approach considerably the solution to the decision-making automation problem under the combine process adjustment in the field environment.

Inspired by quantum theory and reinforcement learning, a new framework of learning in unknown probabilistic environment is proposed. Several simulated experiments are given; the results demonstrate the robustness of the new algorithm for some complex problems. Also we generalized the Grover algorithm to improve the rate of converging to an optimal path. In other words, the new generalized algorithm helps to increase the probability of selecting good actions with better weights' adjustments.

In this work we generalize the Quasi-Minimal Residual Variant of the Bi-CGSTAB algorithm (QMRCGSTAB) to obtain a matrix iterative method for solving the Sylvester-transpose matrix equation ∑ i = 1 l ( A i X B i + C i X T D i ) = E . In order to compare the generalized algorithm with some existing methods, we present two numerical examples.

This article critically reviews the current methodologies for description of enthalpy relaxation dynamics in amorphous materials in the glass transition range. In particular, the description in terms of the Tool–Narayanaswamy–Moynihan (TNM) model is discussed. Advantages and disadvantages of particular methodologies are demonstrated and suggested explanations of possible data-distortive effects involve thermal gradients, improperly designed temperature programs, or incorrectly applied subtraction of the thermokinetic background. In addition, a novel ultimate simulation-comparative method is presented, applicable even for extremely distorted differential scanning calorimetry data. Based on the introduced advantages and disadvantages of particular methodologies, an optimum generalized algorithm for precise and reliable evaluation of TNM parameters is proposed, utilizing both curve-fitting and alternative non-fitting techniques.

Of the four elementary operations, division is the most time consuming and expensive operation in modern day processors. This paper uses the tricks based on Ancient Indian Vedic Mathematics System to achieve a generalized algorithm for BCD division in a much time efficient and optimised manner than the conventional algorithms in literature. It has also been observed that the algorithm in concern exhibits remarkable results when executed on traditional mid range processors with numbers having size up to 15 digits (50 bits). The present form of the algorithm can divide numbers having 38 digits (127 bits) which can be further enhanced by simple modifications.

Current situation in the field of safe chemical handling has been considered. The system approach has been suggested to solve this problem. The functional structure of the information-analytical system of management of safe chemical handling and generalized algorithm for the hazard classification of chemicals have been developed with uncertainty. Examples of the practical use of various classification methods are given, quantitative structure-activity relationships, Euclidean distance, neural networks, and frequency rules.

We introduce and study a new system of generalizedH·,·-η-cocoercive operator inclusions in Banach spaces. Using the resolvent operator technique associated withH·,·-η-cocoercive operators, we suggest and analyze a new generalized algorithm of nonlinear set-valued variational inclusions and establish strong convergence of iterative sequences produced by the method. We highlight the applicability of our results by examples in function spaces.

A generalized algorithm of compensator (Lead/Lag) design, using Root Locus, is proposed for a class of linear systems. The proposed algorithm (set of rules and equations) does not need explicitly drawing the root locus of the plant under consideration and can be a good software tool. The algorithm, takes the performance specifications and plant's data, uses the well known angle and magnitude conditions of the Root Locus technique, decides whether Lead or Lag compensator is needed. The steady state error requirements has also been incorporated (in case of Lag compensator). In addition, the dominance of desired pole pair is guaranteed. The proposed algorithm is verified by numerical examples.

A generalized phase-shifting method for three-wave shearing interferometry is proposed. The phase-shifting algorithm is derived by an optimal process based on least-squares fitting. With this generalized algorithm, the steps of phase-shifting can be reduced to five, which greatly simplifies the measurement and decreases the burden of computation. Both the numerical simulation and the optical experiment are carried out to demonstrate the adaptability of the method.

Traditionally, the convergence rate of the sliding variable given by a discrete reaching law has been fixed in nature. This paper presents a generalized algorithm for discrete time sliding mode control systems which offers a flexible convergence rate for the sliding variable. For analysis, we use the recently developed band approach method which gives us the values of the parameters in the algorithm for the desired convergence to take place, once the ultimate band is chosen appropriately. (C) 2015 Elsevier Ltd. All rights reserved.

In previous chapters we introduced the processes of checking and testing, the first of the three main processes of generalized algorithm of fault tolerance—GAFT. In this chapter we further discuss the process of checking hardware, at first software-based hardware checking and at second hardware-based checking. For the software-based hardware checking, we show what a software-based test should include, when they are the preferred choice over hardware-based checking schemes and especially how such tests can be scheduled in the system without interfering with ongoing real-time tasks. Further to support handling of hardware -based checking we introduce a new system condition descriptor—a so-called syndrome—and illustrate how it can be used as a mechanism to signal to the operating system hardware condition, including manifestation of detected error. We then show the steps the run-time system performs to eliminate the fault and in case of permanent errors how the software can reconfigure the hardware to exclude the faulty element. We also explain in which cases software has to adapt to the new hardware topology. We start by explaining how software-based checks can be used to detect hardware faults. Run-time systems use online or off-line scheduling mechanisms for task management of programs—own—system software ones and user application ones. Since in Kirby et al. (Softw Pract Exp 15(1):87–103, 1985, [2]), Serlin (Comput C 7(8):19–30, 1984, [3]), Blazewicz et al. (Handbook on scheduling, from theory to applications, 2007, [4]), Ingo (Linux kernel archive, 2002, [8]) it is expected that run-time system provides a special session of task scheduling (off-line or online during execution) for the purposes of diagnostic of hardware conditions—recall Apple and Microsoft system starting delays. Later for some systems that operate in domain of real-time monitoring scheduling of tasks, critical in time of execution especially criticality of hardware availability and efficiency of process scheduling, become crucial. In turn testing itself become “hot” in terms of required time and coverage of hardware. Thus in this chapter we initially analyze simple sequences of testing of hardware elements of computer systems. Further, we introduce a concept of transparent for user application procedure of hardware testing. This enables to prove the integrity of computer system hardware, and guarantee it within reasonable time, without delays of service of execution of user tasks.

Fault tolerance so far was considered as a property of a system. In fact and instead we introduce a generalized algorithm of fault tolerance (GAFT) that considers property of fault tolerance as a system process. GAFT implementation analysis—if we want to make it rigorous—should be using classification of redundancy types. Various redundancy types have different “power” of use at various steps of GAFT. Properties of GAFT implementation impact on overall performance of the system, coverage of faults , and ability of reconfiguration. It is clear that separation of malfunctions from permanent fault simply must be implemented and reliability gain is analyzed. A ratio of malfunctions to permanent faults is achieving 105–7 and simple exclusion from working configuration a malfunctioned element is not longer feasible. Further, we have to consider GAFT extension in terms of generalization and application for support of system safety of complex systems. Our algorithms of searching correct state, “guilty” element, and analysis of potential damages become powerful extension of GAFT for challenging applications like avionic systems, aircraft as a whole. In Chap. 3, we showed that fault tolerance should be treated as a process . In this chapter, we elaborate further this process into a clearly defined algorithm and develop a framework to the design of fault-tolerant systems, the generalized algorithm of fault tolerance—GAFT. We also introduce a theoretical model to quantify the impact of the additional redundancy to the reliability of the whole system and derive an answer to the question of how much added redundancy leads to the system with highest reliability. A question that GAFT cannot answer is how the real source of a detected fault can be identified, as the fault manifestation might have occurred in another hardware element and spread in the system due to nonexistent fault containment. We will show an algorithm that based on the dependencies of the elements of a system can identify the possible fault sources and also predict which elements an identified fault might have affected. We now start in a first step by further elaborating the process of fault tolerance .

Fault tolerance so far was considered as a property of a system. In fact and instead we introduce a generalized algorithm of fault tolerance (GAFT) that considers fault tolerance as a system process. There is no doubt we have to analyze GAFT implementation using redundancy types of computer systems. Properties of GAFT implementation impact on overall performance of the system, coverage of faults, and ability of reconfiguration. It is clear that separation of malfunctions from permanent fault simply must be implemented and reliability gain is analyzed. A ratio of malfunctions to permanent faults is achieving 105−7 and simple exclusion from working configuration of a malfunctioned element is no longer feasible. In this chapter, we consider GAFT extension in terms of generalization and application for support of system safety of complex systems. Our algorithms of searching correct state, “guilty” element, and analysis of potential damages become powerful extension of GAFT for challenging applications like avionic systems, aircraft as a whole.

This paper presents a new algorithm that arrives at a generalized solution for the generation of restricted weak compositions of n-parts. In particular, this generalized algorithm covers many commonly sought compositions such as bounded compositions, restricted compositions, weak compositions, and restricted part compositions. Introduced is an algorithm for generating generalized types of restricted weak compositions called first-order, and secondorder restricted weak compositions.

In many fine-grained object recognition datasets, image orientation (left/right) might vary from sample to sample. Since handcrafted descriptors such as SIFT are not reversal invariant, the stability of image representation based on them is consequently limited. A popular solution is to augment the datasets by adding a left-right reversed copy for each original image. This strategy improves recognition accuracy to some extent, but also brings the price of almost doubled time and memory consumptions. In this paper, we present RIDE (Reversal Invariant Descriptor Enhancement) for fine-grained object recognition. RIDE is a generalized algorithm which cancels out the impact of image reversal by estimating the orientation of local descriptors, and guarantees to produce the identical representation for an image and its left-right reversed copy. Experimental results reveal the consistent accuracy gain of RIDE with various types of descriptors. We also provide insightful discussions on the working mechanism of RIDE and its generalization to other applications.

In this paper, the scheduling problem involving optimization of multiple criteria (or objectives) is explored. There are many variants of the problem. The particular variant, in which the objectives are aggregated into a scalar function (with each criterion having weight which denotes its relative importance), is considered. An algorithm which can be used to solve very large classes of the multicriteria scheduling problem is proposed. The proposed algorithm and two solution methods selected from the literature were evaluated on a total of 900 randomly generated multicriteria scheduling problems (ranging from 10 to 500 jobs). Two variants of the release dates (0 – 24 and 0 – 49) are utilized. Results show that the proposed algorithm performed better than the selected solution methods when the total completion time criterion is much more important than the other criteria. However, when the total completion time criterion is much less important than the other criteria, the selected solution methods outperformed the proposed algorithm. The results are consistent under the two variants of the release dates.

Genetic network programming (GNP)-based time-related association rules mining method provides a useful mean to investigate future traffic volume of road networks and hence helps us to develop traffic navigation system. Further improvements have been proposed in this paper about the time-related association rule mining using generalized GNP with multibranches and full-paths (MBFP) algorithm. For fully utilizing the potential ability of GNP structure, the mechanism of generalized GNP with MBFP is studied. The aim of this algorithm is to better handle association rule extraction from the databases with high efficiency in a variety of time-related applications, especially in the traffic volume prediction problems. The generalized algorithm which can find the important time-related association rules is described, and experimental results are presented considering a traffic prediction problem. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

The management of cinematic systems is based on the principle of the assured qualimetric output characteristics of a film. The solution of this problem needs thoroughly elaborated methods and algorithms for processing the expert information that results from the various qualimetric expert evaluations. A generalized algorithm is proposed for processing the expert information that results from the qualimetric expert evaluations of the quality of the cinema-video equipment and film-production services. A list of problems that can be solved using the proposed algorithm is presented.

A nascent theory of near division is presented, from which an efficient quantization algorithm for rhythm intervals is derived. Based on a number theoretic analysis of the uniqueness and convergence of this first algorithm, a generalized algorithm is presented. An empirical study of the algorithm's performance reveals a readily computable criterion within which the perceived ratio may reliably be produced on real performance data. Distribution properties are shown to be reasonable for computation.

Forming effective coalitions is a major research challenge in AI and multi-agent systems (MAS). Coalition Structure generation (CSG) involves partitioning a set of agents into coalitions so that social surplus (the sum of the rewards of all coalitions) is maximized. A partition is called a Coalition Structure (CS). In traditional works, the value of a coalition is given by a black box function called a characteristic function. In this paper, we propose a novel formalization of CSG, i.e., we assume the value of a characteristic function is given by an optimal solution of a distributed constraint optimization problem (DCOP) among the agents of a coalition. A DCOP is a popular approach for modeling cooperative agents, since it is quite general and can formalize various application problems in MAS. At first glance, one might assume that the computational costs required in this approach would be too expensive, since we need to solve an NP-hard problem just to obtain the value of a single coalition. To optimally solve a CSG, we might need to solve n-th power of 2 DCOP problem instances, where n is the number of agents. However, quite surprisingly, we show that an approximation algorithm, whose computational cost is about the same as solving just one DCOP, can find a CS with quality guarantees. More specifically, we develop an algorithm with parameter k that can find a CS whose social surplus is at least max(k/(w*+1), 2k/n) of the optimal CS, where w* is the tree width of a constraint graph. When k=1, the complexity of this algorithm is about the same as solving just one DCOP. These results illustrate that the locality of interactions among agents, which is explicitly modeled in the DCOP formalization, is quite useful in developing an efficient CSG algorithm with quality guarantees.

Features of mutual recognition of national standards, calibration and measurement capabilities (CMC), basic versions and their examination stages are considered. A generalized algorithm is developed for international examination of national metrological institute CMC.

Parallel acquisition of Magnetic Resonance Imaging (MRI) has the potential to significantly reduce the scan time. SENSE is one of the many techniques for the reconstruction of parallel MRI images. A generalized algorithm for SENSE reconstruction and theoretical background is presented. This algorithm can be used for SENSE reconstruction for any acceleration factor between 2 and 8, for any Phase Encode direction (Horizontal or Vertical), with or without Regularization. The user can select a particular type of Regularization. A GUI based implementation of the algorithm is also given. Signal-to-noise ratio, artefact power, and g-factor map are used to quantify the quality of reconstruction. The effects of different acceleration factors on these parameters are also discussed. The GUI based implementation of SENSE reconstruction provides an easy selection of various parameters needed for reconstruction of parallel MRI images and helps in an efficient reconstruction and analysis of the quality of reconstruction. © 2010 Wiley Periodicals, Inc. Concepts Magn Reson Part A 36A: 178–186, 2010.

Some linear dynamical systems over finite fields are studied and the self-similar character of their development is proved. Connections with aperiodic tilings, Delanoy numbers and other topics are also proved. The prime fields F_p have a canonical presentation as sets of self-similar carpets. The multiplicative inverse corresponds to mirroring., 14 pages, some latex figures in text (no separate files) These results have been presented at CiE 2007, Siena, Italy

Using composite cylinders assembly (CCA) model, a generalized algorithm has been developed to evaluate the micro stresses developed in the constituent phases of multiply (N-phases) coated hollow/solid fiber reinforced polymer matrix composites (PMCs) under different hygrothermal loading conditions. In the formulation all the N-phases are considered to be transversely isotropic. Results have been presented for S-glass/epoxy and AS-graphite/epoxy composites treating them as a five-phase (fiber, coating, matrix, and the composite) composite, void being the fifth phase along the centre line of the fiber. Results reveal the differences in the nature and the magnitude of stresses developed when solid fibers are replaced by the hollow ones. The algorithm can be utilized for evaluating the stresses in the constituent phases of multiply coated fiber reinforced metal matrix composites also where more than one coating layer and reaction zones, each with different constituent properties, are to be considered and the composite has to be treated as multiphase composite.

A generalized algorithm is presented for estimating the efficiency of diamond machining of ceramics. The algorithm is based on systematic analysis of the influence of the technological media and the conditions and employs up-to-date computational techniques.

In this work, we employ a Hamiltonian-based procedure to derive a generalized Nose–Hoover thermostat, which generates rigorous trajectories, corresponding to the canonical ensemble, in the absence or presence of external forces. Specifically, we prove that rigorous trajectories are generated regardless of whether the total linear momentum of the system is zero, constant, or time-dependent. Through the use of peculiar and center-of-mass coordinates, we develop a thermostat that is consistent with the definition of temperature through the equipartition theorem. The generalized algorithm reduces to the conventional Nose–Hoover thermostat under the constraints that (i) the external forces are absent and (ii) the total linear momentum is zero. We show that the generalized algorithm satisfies the two criteria for rigor (Hamiltonian and non-Hamiltonian) that exist in the literature. Finally, we provide some numerical examples demonstrating the success of the generalized algorithm.

A new approach to reconstructing the neutron spectra of reactor facilities on the basis of activation measurements is proposed and investigated. A new parameterization of a neutron spectrum is introduced; this representation is in the form of a special “neutron” spline. A generalized algorithm for minimizing the directed deviation is used for the reconstruction. To analyze the possibilities of the approach developed, the spectra of the BARS-5, IGRIK, and YaGUAR reactor facilities are reconstructed on the basis of activation measurements. The reconstructed spectra agree well with previous results.

Infection after total knee arthroplasty remains a potentially devastating complication with substantial consequences. Despite the apparent insecurities relating to the care of an infected arthroplasty, a generalized algorithm has evolved over the last decade that optimizes the diagnosis and treatment of patients with this complication. Several large patient series have demonstrated approximately a 90% success rate when treating infections with a two-stage exchange, which is superior to most series evaluating the results of direct exchange. Two-stage exchange for infected total knee arthroplasty has become the treatment of choice for most joint arthroplasty surgeons in the United States.

In 2006, Blake, Murty and Xu proposed three refinements to Miller’s algorithm for computing Weil/Tate pairings. In this paper we extend their work and propose a generalized algorithm, which integrates their first two algorithms. Our approach is to pre-organize the binary representation of the involved integer to the best cases of Blake’s algorithms. Further, our refinement is more suitable for Solinas numbers than theirs. We analyze our algorithm and show that our refinement has better performance than the original algorithms.

Cost-based metrics formalize notions of distance, or dissimilarity, between two spike trains, and are applicable to single- and multineuronal responses. As such, these metrics have been used to characterize neural variability and neural coding. By examining the structure of an efficient algorithm [Aronov D, 2003. Fast algorithm for the metric-space analysis of simultaneous responses of multiple single neurons. J Neurosci Methods 124(2), 175-79] implementing a metric for multineuronal responses, we determine criteria for its generalization, and identify additional efficiencies that are applicable when related dissimilarity measures are computed in parallel. The generalized algorithm provides the means to test a wide range of coding hypotheses.

In separated notes, we described the mathematical aspects of the potential-Hamiltonian (PH) decomposition, in particular, for n-switches and Liénard systems [J. Demongeot, N. Glade, L. Forest, Liénard systems and potential-Hamiltonian decomposition - I. Methodology, II. Algorithm and III. Applications, C. R. Acad. Sci., Paris, Ser. I, in press]. In the present note, we give some examples of biological regulatory systems susceptible to be decomposed. We show that they can be modelled in terms of 2D ordinary differential equations belonging to n-switches and Liénard system families [O. Cinquin, J. Demongeot, High-dimensional switches and the modeling of cellular differentiation, J. Theor. Biol. 233 (2005) 391-411]. Although simplified, these models can be decomposed into a set of equations combining a potential and a Hamiltonian part. We discuss about the advantage of such a PH-decomposition for understanding the mechanisms involved in their regulatory abilities. We suggest a generalized algorithm to deal with differential systems having a second part of rational-fraction type (frequently used in metabolic systems). Finally, we comment what can be interpreted as a precise signification in biological systems from the dynamical behaviours of both the potential and Hamiltonian parts.

In this study the scheduling supply chain models combination in terms of optimal program control is considered. The SC schedule execution problem is formulated. It is consist of the problem of optimal program control and the problem of positional control. Then for solving considered problem we propose to use mathematical methods of optimal control theory and linear programming, adaptive method. The generalized algorithm is represented and verified on numerical examples.

It is a well documented fact that partial shading increases mismatch losses and reduces the output of a photovoltaic (PV) system. The reduction in output is not proportional to the shaded area but depends on various other factors like the location of the shaded panel within the array, the interconnection among the panels and the shade geometry. The mismatch losses can be reduced either by altering the interconnection scheme or the location of panels in accordance with the shade. These dynamic methods require more number of sensors, switches and a sophisticated control algorithm. This work proposes a static shade tolerant network which enhances the output under shaded conditions by dispersing the shade all over the array. A generalized algorithm to determine the location of panels within the array is also presented. The proposed algorithm and the network are tested for different array sizes and shading conditions in MatLab-Simulink environment and the results are presented.