Динамика приобретения и применения знаний при решении комплексной проблемы по управлению новой системой
Solving a complex problem during interaction with a novel complex system (a virtual factory) is considered from view of dynamics of knowledge acquisition and knowledge application. Performance of successful and non-successful participants is compared based on objective indicators (e.g., profit gained, actions on acquisition of information about the system and actions to control the system, eye movements, etc.) and subjective indicators (participants’ evaluation of various aspects of the problem and performance). Eye tracking has been conducted in the context of classification of participants’ work with: (a) information panels of the factory, and (b) panels with controls. It was postulated that: (a) looking at the information panels is related to knowledge acquisition, and (b) looking at the panels with controls and practical actions on the controls are related to knowledge application. It has been shown that in the initial stages of complex problem solving successful participants set cognitive aims linked to the understanding of the system rather than practical aims (i.e., gaining profit). Non-successful participants set practical aims rather than cognitive ones. When novel variables were introduced into the system successful participants started prioritizing cognitive aims compared to practical aims whereas non-successful participants weakened both cognitive and practical aims. In conclusion, a hypothesis is put forward that success or failure in the management of novel systems can be linked to the type and intensity of cognitive and practical goals which participants set by themselves.
Into the Red explores the emergence of a credit card market in post-Soviet Russia during the formative period from 1988 to 2007. In her analysis, Alya Guseva locates the dynamics of market building in the social structure, specifically the creative use of social networks. Until now, network scholars have overlooked the role that networks play in facilitating exchange in mass markets because they have exclusively focused on firm-to-firm or person-to-person ties. Into the Reddemonstrates how networks that combine individuals and organizations help to build markets for mass consumption. The book is situated on the cutting edge of emerging interdisciplinary research, linking multiple layers of analysis with institutional evolution. Using an intricate framework, Guseva chronicles both the creation of a credit card market and the making of a mass consumer. These processes are placed in the context of the ongoing restructuring in postcommunist Russia and the expansion of Western markets and ideologies through the rest of the world.
Supply chain management is rather new scientific field that reflects the concept of integrated business planning. This concept should be experts and practitioners in logistics and strategic management. Today, integrated planning to become a reality thanks to the development of information technology and computer technology. At the same time to achieve a competitive advantage is not enough high-speed, low-cost data transfer process. In order to effectively apply information technology tools necessary to develop a quantitative analysis of the effectiveness of supply chain management. The mam element of this tool are optimization models that reveal the complex interactions, the wave and the synergies that arise in supply chain management. In this article we consider one of the classes of such models - the so-called dynamic models of conveyor systems, processing of applications.
Uncertainty is a concept associated with data acquisition and analysis, usually appearing in the form of noise or measure error, often due to some technological constraint. In supervised learning, uncertainty affects classification accuracy and yields low quality solutions. For this reason, it is essential to develop machine learning algorithms able to handle efficiently data with imprecision. In this paper we study this problem from a robust optimization perspective. We consider a supervised learning algorithm based on generalized eigenvalues and we provide a robust counterpart formulation and solution in case of ellipsoidal uncertainty sets. We demonstrate the performance of the proposed robust scheme on artificial and benchmark datasets from University of California Irvine (UCI) machine learning repository and we compare results against a robust implementation of Support Vector Machines.
The paper focuses on the concept of ‘financial strategies’ and addresses two problems: first, how to define the concepts of financial strategy and strategizing, and second, how to operationalize them into indicators for empirical research. The introduction to this new concept is based on the conviction that strategizing (which is understood as a specific attitude to life held by people who do not live for the moment, think about their future even if it is rather uncertain, set long-term financial goals and act towards achieving them), is an intrinsic factor in the financial behavior of people. It is argued that it is not possible to define financial strategy or to operationalize it objectively and universally since people operate in very different circumstances; i.e. in different institutional environments or at different stages of life, etc. The solution must be found in the interactionist sociological perspective with the emphasis on the construction of the interpretation of a situation: how individuals themselves make sense of financial strategizing in their own environment, the options they perceive and the constraints they feel.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
Existing approaches suggest that IT strategy should be a reflection of business strategy. However, actually organisations do not often follow business strategy even if it is formally declared. In these conditions, IT strategy can be viewed not as a plan, but as an organisational shared view on the role of information systems. This approach generally reflects only a top-down perspective of IT strategy. So, it can be supplemented by a strategic behaviour pattern (i.e., more or less standard response to a changes that is formed as result of previous experience) to implement bottom-up approach. Two components that can help to establish effective reaction regarding new initiatives in IT are proposed here: model of IT-related decision making, and efficiency measurement metric to estimate maturity of business processes and appropriate IT. Usage of proposed tools is demonstrated in practical cases.
I give the explicit formula for the (set-theoretical) system of Resultants of m+1 homogeneous polynomials in n+1 variables