Simple Software Implementation Research Articles

Performance optimisation techniques for Conflict-free Replicated Data Types (CRDT)

The research relevance is determined by the need for distributed data handling optimisation that does not cause conflicts during replication, since the introduction of such types of data leads to an increase in the need for their optimisation and performance. The study aims to develop techniques to improve the efficiency of various types of data with conflict-free replication. To achieve this goal, the methods of analysis and experimentation were used. The study results demonstrate that the use of certain optimised methods of conflict-free data types in replication leads to a significant improvement in efficiency and reduction of resource costs. The results show that caching and precomputation, asynchronous synchronisation, and local processing are the most effective methods for improving the efficiency of Conflict-free Replicated Data Types. It is established that the choice of a specific method for improving the performance of Conflict-free Replicated Data Types should be justified and based on a careful analysis of the requirements and characteristics of a particular distributed system. This takes into account user needs, data criticality, edit frequency, etc. The research includes the development and optimisation of synchronisation algorithms that significantly improve the performance of these types of data in distributed systems. The work includes simple software implementations for detailed analysis and study of methods for optimising the performance of data types in conflict-free replications. The introduction of distributed computing has made it possible to optimise the processes of data replication and synchronisation, which helps to reduce overheads and improve system performance. It is concluded that the study is of practical importance since the use of optimised conflict-free data types with replication in real distributed systems can improve their efficiency and reliability. The practical significance of the study lies in the possibility of applying optimised methods of data types with conflict-free replication in real distributed systems, which will increase their performance and ensure efficient operation under conditions of high load and limited resource potential

Distributed predictive control based on Gaussian process models

A suboptimal approach to distributed NMPC is proposed based on Gaussian process models of the interconnected systems dynamics and taking into account the imposed constraints. The suggested method is based on a sequential linearization of the nonlinear system dynamics and finding a suboptimal solution of the resulting Quadratic Programming (QP) problem by using distributed iterations of the dual accelerated gradient method. The main advantages of the distributed approach are that it allows the computation of the suboptimal control inputs to be done autonomously by the subsystems without the need for centralized optimization and it has a simple software implementation. The proposed method is illustrated with simulations on the simplified model of a sewer system.

Алгоритм оцінювання частоти комплексного гармонічного сигналу з сегментацією даних спостережень

The article deals with the technology of estimating the frequency of harmonic components in the presence of additive normal interferences for solving applied problems of spectral analysis. Objective: to develop a methodology for the synthesis of algorithms for determining the frequency of a complex harmonic signal in discrete sections of the process, this is observed when using data segmentation. Objective: to develop the optimal technology for determining the frequency of the hormonal component of the process, provided by a finite number of discrete compartments, according to model representations and requirements that meet the problems of the current state of spectral analysis practice. These results were obtained. The problem of estimating the harmonic frequency from segmented data in the presence of additive Gaussian interference in observations based on the method of maximum likelihood is solved. The processing algorithm and the consequences of digital modeling of the synthesized evaluation technology for a given number of discrete process samples are given. The analysis of both the practical capacity of the technology for determining the assessment and certain qualitative indicators of assessment is performed. Conclusions. The scientific novelty of the obtained results is as follows: further development as a method for solving problems of estimating the frequency of the harmonic signal from a few sample values of the process under conditions of additive normal interference and methods for optimizing the structure of digital processing of observations in data segmentation. The synthesized technology uses one sample of observations to determine the estimates, which ensure the efficiency of information processing in a simple software implementation. The use of segmentation in the technological process of digital processing of observations allows obtaining estimates, the quality of which corresponds to the indicators of maximum likelihood. For unambiguous assessment, there is a need to eliminate ambiguity. Under these conditions, the technology with a given number of samples can significantly solve the range of signal-to-noise ratios at which can be obtained unbiased estimates.

Two-stage segment linearization as part of the thermocouple measurement chain

An implementation of a two-stage piece-wise linearization method for reduction of the thermocouple approximation error is presented in the paper. First, the whole thermocouple measurement chain of a transducer is described, and possible error is analysed to define the required level of accuracy for linearization of the transfer characteristics. Evaluation of linearization functions and analysis of approximation errors are performed by the virtual instrumentation software package LabVIEW. The method is appropriate for thermocouples and other sensors where nonlinearity varies a lot over the range of input values. The basic principle of this method is to first transform the abscissa of the transfer function by a linear segment look-up table in such a way that significantly nonlinear parts of the input range are expanded before a standard piece-wise linearization. In this way, applying equal-segment linearization two times has a similar effect to non-equal-segment linearization. For a given examples of the thermocouple transfer functions, the suggested method provides significantly better reduction of the approximation error, than the standard segment linearization, with equal memory consumption for look-up tables. The simple software implementation of this two-stage linearization method allows it to be applied in low calculation power microcontroller measurement transducers, as a replacement of the standard piece-wise linear approximation method.

DEADLOCK ALGORITHM FOR ADVANCED SYNTACTICAL ANALYSIS AND ITS APPLICATION TO PROGRAMMING LANGUAGES FOR QUANTUM COMPUTERS

When developing promising programming languages designed to support the work of supercomputers, including quantum ones, there is a need for research related to testing the developed language under conditions when parsers do not yet exist for it. In particular, in the process of developing a programming language for a quantum computer, it becomes necessary to parse a certain program written in a new programming language, which, like all programming languages, belongs to the class of context-free languages (cf-languages). The problem of syntactical analysis of the monomials of cf-languages was posed in the 50-60s of the last century, however, there are some discrepancies in its formulation, and therefore there is a need to clarify the formulation of this problem. In this regard, we will call the expanded problem of parsing the problem of developing a stupid (non-stop, irrevocable) algorithm that allows establishing whether a given monomial can be deduced using a system of products that form a cf-language grammar, and also find all the conclusions of this monomial at once if the latter exists. The description of the monomial inference is understood as follows: it is necessary to determine for which products from the grammar of the cf-language, how many times and in what order they are used to derive this monomial, which is equivalent to constructing all the output trees. The article has developed a deadlockless algorithm for solving the extended problem of parsing, based on the method of hierarchy of marked brackets. The marked brackets order shows what products they are assigned to, and allows you to trace the order of its use. The algorithm uses the method of successive approximations to solve the Chomsky-Schützenberger system of equations associated with the cf-language grammar. The developed algorithm has a simple software implementation; an assessment of the complexity of the algorithm is also given.

High Performance Distribution Network Power Flow Using Wirtinger Calculus

The power flow problem can be compactly formulated using complex variables; its solution is however commonly computed using the real variable Newton-Raphson algorithm, where the complex variables are replaced by their real valued rectangular or polar coordinates. A Newton-Raphson solution in complex variables is hindered by the fact that the power flow equations are non-analytic in their phasor voltages, i.e., they do not have a Taylor series expansion in terms of these complex variables alone. By using Wirtinger calculus, the power flow equations can be expanded in terms of the phasor voltages and their conjugates, thus allowing the implementation of the complex variable Newton-Raphson algorithm. This paper specializes the solution of the complex variable Newton-Raphson power flow to distribution networks, and includes the particularities of modeling line drop compensators, reactive power limited generation, and voltage dependent loads. Numerical results presented on distribution networks with up to 3139 nodes show that the complex implementation is better suited to modern processors that employ single instruction multiple data (SIMD) processor extensions; in particular SIMD instructions result in a complex variable formulation that is faster than the classical real variable formulation, yet it has the distinct advantage of a simple software implementation.

Distributed Nonlinear Model Predictive Control by Sequential Linearization and Accelerated Gradient Method

A suboptimal approach to distributed NMPC for nonlinear interconnected systems subject to constraints is proposed. The objective is to develop a computationally efficient approach. The suggested method is based on a sequential linearization of the nonlinear system dynamics and finding a suboptimal solution of the resulting Quadratic Programming problem by using distributed iterations of the dual accelerated gradient method. The benefits of the approach are reduced complexity of the on-line computations, and simple software implementation, which makes it appropriate for embedded distributed convex NMPC. The proposed method is illustrated with simulations on the model of a quadruple-tank system.

Reconstruction and selection of J/ψ → e + e − decays registered by CBM setup in 25 AGeV AuAu collisions

The problem of reconstructing and selecting J/ϕ → e+e− decays registered by the CBM setup in AuAu collisions at 25 AGeV beam energy is considered. The key task in this problem is fast and reliable electron-positron identification using the energy losses of charged particles in the Transition Radiation Detector (TRD). We consider two methods for solving this problem: an artificial neuron network (ANN) and a modified non-parametric goodness-of-fit ωnk criterion. Our analysis shows that both approaches give similar results for the J/ϕ → e+e− yield and the signal-to-background ratio. Compared with the ωnk criterion, the method based on ANN has a number of disadvantages which are discussed in detail. Taking into consideration the very simple software implementation of the ωnk algorithm, it can be used for J/ϕ → e+e− decays selection in a real-time experiment.

Postprandial blood glucose control using a hybrid adaptive PD controller with insulin-on-board limitation

This paper addresses the design of blood glucose control during the postprandial period for Type 1 diabetes patients. An artificial pancreas for ambulatory purposes has to deal with the delays inherent to the subcutaneous route, the carbohydrate intakes, the metabolic changes, the glucose sensor errors and noise, and the insulin pump constraints. A time response typically obtained in closed-loop insulin delivery shows hyperglycemia in the early postprandial period caused by the lag in the insulin absorbtion, followed by hypoglycemia caused by control over-reaction. A hybrid control system is proposed in this paper to overcome these problems. An insulin bolus is administered prior to the meals like in open-loop control, whereas a PD controller is used for robust glucose regulation. The controller gain is progressively increased after the bolus from zero up to its nominal value as function of the insulin on board, so that the PD controller becomes fully operational just when the insulin on board falls below a prescribed value. An excessive accumulation of active insulin is avoided in this way, drastically reducing the risk of hypoglycemia. The controller gain is adapted by means of a variable structure algorithm, allowing a very simple software implementation. The robust performance of the control algorithm is intensively assessed in silico on a cohort of virtual patients under challenging realistic scenarios considering mixed meals, circadian variations, time-varying uncertainties, discrete measurement and actuation, sensor errors and other disturbances.

Numerical analysis of the spiral Couette flow of a rarefied gas between coaxial cylinders

An implicit quasi-monotone second-order accurate method is proposed for analyzing the spiral Couette flow of a rarefied gas between coaxial cylinders. The basic advantages of the method over the conventional method of stationry iterations are that the former is conservative with respect to the collision integral, has a simple software implementation for any types of boundary conditions, and applies to a wide range of Knudsen numbers.

ERP integration in a healthcare environment: a case study

PurposeAims at providing a classification of the ERP integration concept in a healthcare organization and at presenting a real world example of process integration using SAP R/3.Design/methodology/approachResearch is based on a case study involving in‐depth semi‐structured interviews with key stakeholders and action research conducted in the hospital during the ERP implementation period.FindingsFindings suggest that an apparently simple software implementation of an ordering process can have a considerable impact on stakeholders in a complex environment operating ERP software. Organizational change issues, implementation and integration issues of SAP R/3 with other non‐SAP systems and SCM considerations are discussed.Originality/valueAnalyzes enterprise integration concept specifically in a healthcare environment and describes a real world process integration solution (missing from the literature) achieved by using SAP R/3 software.

On some systems of generators of symmetric and alternating groups which allow a simple software implementation

We give systems of generators of symmetric and alternating permutation groups whose software implementation relies upon simple arithmetical operations. For some given systems, we estimate the group depth (the generator system index).

On some systems of generators of symmetric and alternating groups which allow a simple software implementation

We give systems of generators of symmetric and alternating permutation groups whose software implementation relies upon simple arithmetical operations. For some given systems, we estimate the group depth (the generator system index).

On some systems of generators of symmetric and alternating groups which allow a simple software implementation

On some systems of generators of symmetric and alternating groups which allow a simple software implementation

Software Design of System Requirements Utilizing Set Theory Model for Anomaly Handling

AbstractIn 1995 Ronald Carson developed a mathematical model for system requirements analysis (SRA) utilizing set theory to explicitly treat unwanted or unexpected conditions that may be experienced by the system being analyzed. He showed that the SRA model can be used to derive completeness criteria. He claimed that the highest utility of the model would be found in the area of software requirements because of the focus on system states.A simple example using a Power Distribution Unit (PDU) was made in order to clarify the salient points. This simple example had only three states and six transitions, which were identified as nine antecedents (conditions which precede). Eight requirements were generated for the PDU.In this paper, the requirements for this simple example, along with its principles, are used to construct a simple software implementation in graphical fashion in order to test the effectiveness of the methodology for software.In conclusion, the SRA model utilizing elementary set theory needs some refinement for software applications. Though the method is rigorous, problems surface because of 1) ambiguities in language, 2) unforeseen conditions, 3) undefined initial conditions, and 4) probability density function of primitives.In addition, the start condition of the timers are undefined, as are the initial states of primitives, e.g. valid input, degraded input and inhibit output and degraded output.

Numerical modelling and simulation of hysteresis effects in magnetic cores using transmission-line modelling and the Preisach theory

The transmission line modelling method and the Preisach theory are employed to model and simulate the hysteresis effects of magnetic cores. This combined approach provides a useful method, which allows fast and accurate prediction of magnetic core losses, and simple software implementation of the dynamic discrete model. The model can be developed easily, using data provided by core manufacturers and simple measurements. This paper describes, in a tutorial style, the numerical aspects and software implementation of the modelling and simulation of hysteresis for a magnetic core. Step-by-step procedures of the modelling and simulation are included, and demonstrated in a computer simulation. Both simulated and measured results are presented.

Space instrument neural network for real-time data analysis

A simple software implementation of an artificial neural network (ANN) was used to analyze up to 200 autocorrelation functions (ACFs) per second within the Shuttle Potential and Return Electron Experiment (SPREE) flown on the Shuttle STS46 mission, July 31, 1992. As all ACF data are stored onboard until postmission, this facility provided ground-based experimenters with their only access to ACF data in real time for optimum instrument control. ACFs contain data either as waveforms or as radar echoes. Operating directly on the ACF, the neural network identifies the type of data, ascertains the wave frequency or radar peak separation, and provides a score or measure of significance of its decision. An effective 16:1 data reduction is achieved and the data interpretation performance is comparable to that achieved by an expert data analyst. Erroneous analysis accounts for less than 1% of data analyzed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

A scalable implementation of barrier synchronization using an adaptive combining tree

Barrier synchronization is commonly used for synchronizing processors prior to a join operation and to enforce data dependencies during the execution of parallelized loops. Simple software implementations of barrier synchronization can result in memory hot-spots, especially in large scale shared-memory multiprocessors containing hundreds of processors and memory modules communicating through an interconnection network. A software combining tree can be used to substantially reduce memory contention due to hot-spots. However, such an implementation results inO(logn) latency in recognition of barrier synchronization, wheren is the number of processors. In this paper anadaptive software combining tree is used to implement a scalable barrier withO(1) recognition latency. The processors that arrive early at the barrier adapt the combining tree so that it has a structure appropriate for reducing the latency for the processors that arrive later. We also show how adaptive combining trees can be used to implement the fuzzy barrier. The fuzzy barrier mechanism reduces the idling of processors at the barriers by allowing the processors to execute useful instructions while they are waiting at the barrier.