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An age-structured bioeconomic model, which is completely continuous in age and time, is developed in order to compare with traditional discrete models. Both types have advantages and disadvantages. The continuous framework complements discrete models as it allows for deeper and more transparent analytical study and leads to analytical results that would be difficult to achieve within a discrete framework. To make the model realistic, a nonlinear recruitment function is introduced and steady state solutions and constant-effort optimal fishing are studied analytically. In addition, the framework has been used for numerical analysis. Simulations are used to investigate how optimal harvesting patterns vary with parameter values.
Mathematical modeling of a stock market functioning is one of the actual and at the same time complex task of the modern theoretical economics. From our point of view, building such mathematical models “ab initio”, by using analogy between the stock market and a certain physical system (in our work, laser), is the most promising approach. This paper proposes a simple econophysical model of stock market as an open nonequilibrium system in form of Lorenz–Haken equation. In this system, variation of ask price, variation of bid price, and instantaneous difference between numbers of agents in active and passive state are intensity of external information flow is a control parameter. This model explains the impossibility of existence of an equilibrium state of the market and shows the presence of deterministic chaos in a stock market.
This book contains a selection of papers accepted for the presentation and discussion at the 2018 International Conference on Digital Science (DSIC’18). This Conference had the support of the Institute of Certified Specialists, Russia, AISTI (Iberian Association for Information Systems and Technologies), and Springer. It will take place Convention Centre, Budva, Montenegro, October 19-21, 2018.
DSIC’18 is an international forum for researches and practitioners to present and discuss the most recent innovations, trends, results, experiences, and concerns in the several perspectives of Digital Science. The main idea of this Conference is that the world of science is united allowing all scientists/practitioners to be able to think, analyze, and generalize their thoughts.
DSIC aims efficiently to disseminate original research results in natural, social, art, and humanities sciences. An important characteristic feature of the Conference should be the short publication time and worldwide distribution. This Conference enables fast dissemination, so conference participants can publish their papers in print and electronic format, which is then made available worldwide and accessible by numerous researchers.
The Scientific Committee of DSIC’18 was composed of multidisciplinary group of 26 experts. One hundred and seven invited reviewers who are intimately conceded with Digital Science have had the responsibility for evaluating, in a “double-blind review” process, the papers received for each of the main themes proposed for the Conference: Digital Art and Humanities; Digital Economics; Digital Education; Digital Engineering, Digital Environmental Sciences; Digital Finance; Business and Banking; Digital Media; Digital Medicine; Pharma and Public Health; Digital Public Administration; Digital Technology and Applied Sciences.
DSIC’18 received 88 contributions from 16 countries around the world. The papers accepted for the presentation and discussion at the Conference are published by Springer (this book) and will be submitted for indexing by ISI, SCOPUS, among others.
Distinguishing outliers from normal data in wireless sensor networks has been a big challenge in the anomaly detection domain, mostly due to the nature of the anomalies, such as software or hardware failures, reading errors or malicious attacks, just to name a few. In this article, we introduce an anomaly detection-based OPF classifier in the aforementioned context. The results are compared against one-class support vector machines and multivariate Gaussian distribution. Additionally, we also propose to employ meta-heuristic optimization techniques to finetune the OPF classifier in the context of anomaly detection in wireless sensor networks.
Previous works by these authors offer the numerical methodof successive approximations for developing the solutionsof the problemof stabilization of nonlinear systems with standard functional. This paperconsiders applying this method for studying the problem with singularcontrol. It is achieved by introducing an auxiliary problem. The solutionfor the auxiliary problem provides smooth approximation tothe solutionof the initial problem. The paper presents the algorithms for constructingan approximate solution for the initial problem. It is demonstrated that,unlike direct algorithms of optimal control, these algorithms allow toregister the saturation point, thus enabling one to register and studysingular regimes.
This paper suggests an algorithm for stress testing of the credit risk of a Russian commercial bank, intended for use by investors and bank customers to assess the bank’s financial stability under stressful scenarios. Indicator of bank losses in this work is the indicator “loan loss provision”. An algorithm is proposed that describes the bank’s cash flows in stressful situations, taking into account the demand function for the loans of the analyzed bank, the bank’s availability of the necessary capital to increase the loan portfolio, and the availability of a sufficient amount of liquid to cover losses.
Sustaining a competitive edge in today’s business world requires innovative approaches to product, service, and management systems design and performance. Advances in computing technologies have presented managers with additional challenges as well as further opportunities to enhance their business models.
Software Engineering for Enterprise System Agility: Emerging Research and Opportunities is a collection of innovative research that identifies the critical technological and management factors in ensuring the agility of business systems and investigates process improvement and optimization through software development. Featuring coverage on a broad range of topics such as business architecture, cloud computing, and agility patterns, this publication is ideally designed for business managers, business professionals, software developers, academicians, researchers, and upper-level students interested in current research on strategies for improving the flexibility and agility of businesses and their systems.
This paper deals with the implementation of numerical methods for searching for traveling waves for Korteweg–de Vries-type equations with time delay. Based upon the group approach, the existence of traveling wave solution and its boundedness are shown for some values of parameters. Meanwhile, solutions constructed with the help of the proposed constructive method essentially extend the class of systems, possessing solutions of this type, guaranteed by theory. The proposed method for finding solutions is based on solving a multiparameter extremal problem. Several numerical solutions are demonstrated.
A simple sociophysical model is proposed to describe the transition between a chaotic and a coherent state of a microblogging social network. The model is based on the equations of evolution of the order parameter, the conjugated field, and the control parameter. The self-consistent evolution of the networks is presented by equations in which the correlation function between the incoming information and the subsequent change of the number of microposts plays the role of the order parameter; the conjugate field is equal to the existing information; and the control parameter is given by the number of strategically oriented users. Analysis of the adiabatic approximation shows that the second-order phase transition, which means following a definite strategy by the network users, occurs when their initial number exceeds a critical value equal to the geometric mean of the total and critical number of users.
The sanctions imposed against Russia in 2014 coincided with a shock in the oil market. It is believed that both the sanctions and the fall in prices over oil have affected both the ruble exchange rate, which devalued by 2 times in relation to the pre-crisis level. The authors of the article assess the impact of sanctions on the ruble exchange rate using ensemble empirical mode decomposition and Hurst exponent. Based on the theory of an effective market, the results of the article shown that in 2014–2015 there was no direct impact of sanctions on the ruble exchange rate. Additionally, the impact of panic in the foreign exchange market on the exchange rate has been estimated, and it is also shown that the foreign exchange market has a long memory.
This article describes modern methods of data processing regarding the task of assessing activities of transportation employees. The main purpose was to find dependencies in data and construct an algorithm for predicting the probability of transport safety violation by employee. The research was conducted for locomotive drivers. The following algorithms were used: neural networks, gradient boosting over decision trees and random forest. Based on the obtained results and drawn conclusions one can think of the perspective for the elaboration and introduction this work for practical use in railway industry, e.g. in “Russian Railways”.
In recent years more and more participants of the retail segment of the banking sector of Russia are launching platform-based value chains along with traditional linear value chains. As a result, business organizations are transforming into a complex system within which customers, banks and retail chains enter into business relations with each other as well as the platform itself, the owner of which is one of the participants of this interaction. A new kind of value exchange is the result of this which has become possible due to the existence of the platform. Platforms complement and compete with linear value chains in order to attract customers. In this article a comparison of these two types of value chains is presented using the example of purchasing goods by installments in Russia, their peculiar workings are also distinguished.
A fridge plays an important role in the kitchen in comparison to other appliances because it helps to store food products at optimal conditions for a long period of time. The ordinary refrigerators perfectly allow preserving meals but they are not effective in case of food management. Providing a remote control for home appliances extends the everyday usage of these devices. In addition to the remote control device, some manufacturers use additional modules such as internal cameras and hands-free speaker for convenient control of an appliance. All these devices are able to communicate with each other to reach common goals. The home appliance producer Liebherr in cooperation with technology company Microsoft developed a solution for remote control of refrigeration with possibility of food recognition using Machine Learning algorithms. This option enables automatic compiling of the list of food stored in the fridge and food ordering in an online shop without manual actions. This opportunity enables not only a convenient usage of an appliance but also allows reduction of electricity consumption because user does not open fridge doors frequently as far as he knows a list of food in refrigerator. In this paper we describe SmartDevice technology from Liebherr that was developed for adding smart features to the brand products. In particular, we review main business processes of SmartDevice, discuss advantages and disadvantages of this solution for the end customers and identify future research for creating smart fridges.
A modern enterprise has to react to permanent changes in the business environment by transformation of its own behavior, operational practices and business processes. Such transformations may range from changes of business processes to changes of information systems used to support the business processes, changes in the underlying IT infrastructures and even in the enterprise information system as a whole. The main characteristic of changes in a turbulent business environment and, consequently, in the enterprise information system is unpredictability. Therefore, an enterprise information system should support the operational efficiency of the current business model, as well as provide the necessary level of agility to implement future unpredictable changes of requirements.
This article aims to propose a conceptual model of an agile enterprise information system, which is defined as a working system that should eliminate the largest possible number of gaps caused by external events through incremental changes of its own components. A conceptual model developed according to the socio-technical approach includes structural properties of an agile enterprise information system (actors, tasks, technology, and structure). Structural properties define its operational characteristics, i.e. measurable indicators of agility – time, costs, scope and robustness of process of change. Different ways to build such an agile system are discussed on the basis of axiomatic design theory. We propose an approach to measurement of time, cost, scope and robustness of changes which helps to make quantitative estimation of the achieved level of agility.
We consider interior and exterior initial boundary value problems for the three-dimensional
wave (d’Alembert) equation. First, we reduce a given problem to an equivalent operator
equation with respect to unknown sources deﬁned only at the boundary of the original
domain. In doing so, the Huygens’ principle enables us to obtain the operator equation
in a form that involves only ﬁnite and non-increasing pre-history of the solution in time.
Next, we discretize the resulting boundary equation and solve it eﬃciently by the method
of difference potentials (MDP). The overall numerical algorithm handles boundaries of
general shape using regular structured grids with no deterioration of accuracy. For long
simulation times it offers sub-linear complexity with respect to the grid dimension, i.e., is
asymptotically cheaper than the cost of a typical explicit scheme. In addition, our algorithm
allows one to share the computational cost between multiple similar problems. On multi-
processor (multi-core) platforms, it beneﬁts from what can be considered an effective
parallelization in time.
Researchers face fundamental challenges applying the stochastic geometry framework to analysis of terahertz (THz) communications systems. The two major problems are the principally new propagation model that now includes exponential term responsible for molecular absorption and blocking of THz radiation by the human crowd around the receiver. These phenomena change the probability density function (pdf) of the interference from a single node such that it no longer has an analytical Laplace transform (LT) preventing characterization of the aggregated interference and signal-to-interference ratio (SIR) distributions. The expected use of highly directional antennas at both transmitter and receiver adds to this problem increasing the complexity of modeling efforts. In this paper, we consider Poisson deployment of interferers in ℜ 2 and provide accurate analytical approximations for pdf of interference from a randomly chosen node for blocking and non-blocking cases. We then derive LTs of pdfs of aggregated interference and SIR. Using the Talbot’s algorithm for inverse transform we provide numerical results indicating that failure to capture atmospheric absorption, blocking or antenna directivity leads to significant modeling errors. Finally, we investigate the response of SIR densities to a wide range of system parameters highlighting the specific effects of THz communications systems. The model developed in this paper can be used as a building block for performance analysis of realistic THz network deployments providing metrics such as outage and coverage probabilities.
This study concerns the use of crypto-currency with specific reference to the situation in Russia. A variety of such systems exist; Bitcoin, however, is perhaps the best-known example and will be used as synonymous with the concept throughout this article. Our findings not only show how the views of Russian government bodies are formed and developed, but also sheds light on the specific innovative methods which legal entities use for development of the economy. Consideration will be given to recent developments within Russia which has been more active than many countries in seeking to clarify the status of Bitcoin and providing for the regulation of the technology.