Mikhail Yu. Kataev

Toward Risk Reduction for Mobile Service Composition

The advances in mobile technologies enable us to consume or even provide services through powerful mobile devices anytime and anywhere. Services running on mobile devices within limited range can be composed to coordinate together through wireless communication technologies and perform complex tasks. However, the mobility of users and devices in mobile environment imposes high risk on the execution of the tasks. This paper targets reducing this risk by constructing a dependable service composition after considering the mobility of both service requesters and providers. It first proposes a risk model and clarifies the risk of mobile service composition; and then proposes a service composition approach by modifying the simulated annealing algorithm. Our objective is to form a service composition by selecting mobile services under the mobility model and to ensure the service composition have the best quality of service and the lowest risk. The experimental results demonstrate that our approach can yield near-optimal solutions and has a nearly linear complexity with respect to a problem size.

A Clustering-Based Approach to Enriching Code Foraging Environment

Developers often spend valuable time navigating and seeking relevant code in software maintenance. Currently, there is a lack of theoretical foundations to guide tool design and evaluation to best shape the code base to developers. This paper contributes a unified code navigation theory in light of the optimal food-foraging principles. We further develop a novel framework for automatically assessing the foraging mechanisms in the context of program investigation. We use the framework to examine to what extent the clustering of software entities affects code foraging. Our quantitative analysis of long-lived open-source projects suggests that clustering enriches the software environment and improves foraging efficiency. Our qualitative inquiry reveals concrete insights into real developers behavior. Our research opens the avenue toward building a new set of ecologically valid code navigation tools.

An evolving trajectory – from PD, logistics, SCM to the theory of material flow

The growing interest in the material flow (MF) theory has invoked much interesting research in recent years. Although the MF theory is relatively new, a review of the related literature from a historical perspective shows that MF theory represents a new stage of the evolutionary development of interrelated subjects such as Physical Distribution (PD), Logistics, and Supply Chain Management (SCM). The purpose of this paper is to provide a summative review of the evolution of the subjects of PD, Logistics, and SCM, and their new development, MF theory. The paper aims at tracing how concepts and findings in PD, Logistics, SCM, and MF have been developed and have evolved. The study shows that PD evolved to Logistics in middle of the 1980s; starting from the late 1990s, Logistics has evolved to SCM; and today PD, Logistics, and SCM can be considered to be under the umbrella provided by a new theory called MF theory. This paper points out that MF theory is a necessity to deal with the overwhelming complexity of ...

A new compound arithmetic crossover-based genetic algorithm for constrained optimisation in enterprise systems

ABSTRACT In many real industrial applications, the integration of raw data with a methodology can support economically sound decision-making. Furthermore, most of these tasks involve complex optimisation problems. Seeking better solutions is critical. As an intelligent search optimisation algorithm, genetic algorithm (GA) is an important technique for complex system optimisation, but it has internal drawbacks such as low computation efficiency and prematurity. Improving the performance of GA is a vital topic in academic and applications research. In this paper, a new real-coded crossover operator, called compound arithmetic crossover operator (CAC), is proposed. CAC is used in conjunction with a uniform mutation operator to define a new genetic algorithm CAC10-GA. This GA is compared with an existing genetic algorithm (AC10-GA) that comprises an arithmetic crossover operator and a uniform mutation operator. To judge the performance of CAC10-GA, two kinds of analysis are performed. First the analysis of the convergence of CAC10-GA is performed by the Markov chain theory; second, a pair-wise comparison is carried out between CAC10-GA and AC10-GA through two test problems available in the global optimisation literature. The overall comparative study shows that the CAC performs quite well and the CAC10-GA defined outperforms the AC10-GA.

A new attribute reduction method and its application in covering information systems

ABSTRACT This paper focuses on removing information redundancy from a covering information system. First, we review the common covering reduction methods and discussed their relationship to each other. Second, we consider the explicit and implicit values of compound attributes in order to lay the basis of our work. Then we obtain a network topology of covering. Third, we prove that network topology is a set of bases in a covering information system through an example, in which we obtain all the irreducible elements. Finally, we discuss the network topology-based attribute reduction method, as well as compare it with other methods. Our discussions enrich the existing attribute reduction theories and methods.

Computer realization of estimations of the atmospheric anomalies caused by gas-aerosol pollution of the near-ground atmosphere

In the paper, algorithms of the techniques incorporated in subsystems of the program complex are presented for calculation and estimation of atmospheric anomalies, caused by industrial emissions in the atmosphere. The complex is included in the gas analyzer DAN-2, developed for registration of emission and absorption of optical and the microwave radiation initiated by gas-aerosol pollution in the atmosphere. The complex DAN-2 has been developed in the Institute of Atmospheric Optics of the Siberian Branch of the Russian Academy of Science. Techniques include: calculation of gas concentration in a plume of industrial emission taking into account gas-aerosol attenuation, an azimuth of the device sighting at a direction of the source and the allocated illumination of the day-time sky; numerical modeling of formation and distribution of gas-aerosol emission fields in the atmosphere with use of various models (Gaussian, Berlyand, etc); the forecast of optical noise in the atmosphere at operating hardware DAN-2 taking into account different types of underground surfaces under various hydro meteorological conditions; algorithm of restoration of the plume structure under its image. In the paper, results of testing of the specified algorithms are presented with use of the data of natural measurements of NO2 and SO2 concentration in the emission plume of the thermal power station GRES-2 in Tomsk, which were received by the complex DAN-2. Calculation of atmospheric background noise and distributions of the gas-aerosol plume has been carried out by various methods with use of these data.

An analysis of methods of atmospheric gas concentration retrieving from diode laser measurements

Atmospheric gas tunable diode laser (TDL) monitoring scheme is sensitive, local, real-time and portable. The traditional spectrophotometric methods have more performances for gas analysing, but are slow in response in high spectral resolution scheme and depend on influences by different gas species. Local measurements of small atmospheric gas components concentration (CH4, CO, etc.) with diode-laser spectrometers are widely used in various of science and technical applications. An inverse task is usuallu solved by the correlation method (using all the measurement wavelengths) or other methods (for example, the method of fitting of the recorded spectrum under modelling). Each of these approaches has restrictions on retrieving connected with the features of measurement methods used in practice. This report, the results of the different inverse methods for retrieving the methane concentration from the data of a diode-laser spectrometer working in the NIR spectral range are analyzed. The methane diode-laser detector has a reference cell (with the known methane concentration) and a cross-flow cell (atmospheric air) as shown in Fig.1. The program of control and data processing of measurements is written with help of LabView software.

Empirical orthogonal functions and its modification in the task of retrieving of the total amount CO2 and CH4 with help of satellite fourier transform spectrometer GOSAT (TANSO-FTS)

The article describes the modification of the empirical orthogonal functions method for solving of the inverse task (retrieving of the total amount CO2) of the real data processing of the satellite instrument (Fourier transform spectrometer medium resolution) GOSAT. Presents the results of the processing of the GOSAT data for the USA territory monitoring stations Lamont and Park Falls (TCCON network).

Application of the neural network approach for retrieving of gas concentration from CO 2 -laser data

In the report a method of atmospheric gases concentration retrieving from the C02-laser gas analyser data on the basis of neural networks (NN) is description. The method of neural networks is compared to the known method of the least squares most frequently meeting at processing of laser signals. One of the problems arising at processing of the lidar signals is stability of the solving (gas concentration) depending on random mistakes of measurement. A method of the neural network as have shown results of numerical modeling, it is possible to relate to a stable method of retrieving of gases concentration from C02-laser data.

Application of neural networks for retrieving atmospheric gases concentration profile for lidar sounding data

In the report a method of ozone profile concentration retrieving from the lidar data sounding on the basis of neural networks (NN) is description. Application of neural networks in inverse tasks is connected with solving some important stages. In the first, it is necessary to carry out training of NN on the basis of the big data set (measurement - decision). In the second, basing on the results of the first stage to generate optimum NN (number of layers, transfer functions). Results of simulation inverse task of ozone profile concentration retrieving from the lidar data sounding have shown reliability of work in NN, speed of the inverse tasks solving and accuracy of retrieving ozone profile comparable to traditional methods.