Systematisation of Corporate Planning

The systematization of corporate planning is a subject that provokes the research interest due to the increased importance of strategic and long-term planning for the corporate development. This article analyzes some problem areas related to the differences between the essence and the procedures of long-term and strategic company planning. The aim is to highlight some views of strategic and long-term planning in companies and the distinguishing features between these categories, draw the attention of contemporary managers to pursuing and combining different methods depending on the characteristics of the company’s activity and the environment in which it operates.corporate planning; management; strategic decisions; firm economic.

Dynamics of the Financial Wealth of the Institutional Sectors in Bulgaria: Empirical Studies of the Post-Communist Period

The question of who benefits and who loses from the transition, the channels and mechanisms of redistribution of wealth in the post-communist period, and the relation between redistribution and monetary regime are, in our opinion, fundamental in understanding theoretically the deep systemic changes in Eastern Europe. This article has two basic tasks ñ one empirical and one theoretical. Our empirical task is to analyse the dynamics of the financial wealth of the institutional sectors in Bulgaria in the period 1998-2005 and to identify the major net creditors and net debtors. The empirical data used for the purpose are based on adapted methodology for the financial account of the Bulgarian economy according to the requirements of the System of National Accounts (SNA). Econometric simulations have been carried out of the major factors conditioning the change in the sectoral financial wealth. The empirical investigations are given in Part 3. Our theoretical task is to prove the hypothesis (which is to a large extent supported by the empirical results) about the functional relationship between the dynamics of redistribution and the change in monetary regime. This is presented in Part 2 and is discussed in Part 4.http://deepblue.lib.umich.edu/bitstream/2027.42/57244/1/wp864 .pd

Information Provision for Strategic Planning in Bulgarian SMEs

The information provision of strategic planning in small and medium sized enterprises (SMEs) is a subject that provokes the research interest due to the increased importance of strategic planning for the corporate development. This article - based on the results of a survey among 50 SMEs in Rousse region (Bulgaria) - analyzes some problem areas related to practical implementation of the concept of strategic business planning, and in particular the practice of providing information for solving strategic issues in SMEs. The aim is to highlight some typical information sources for the strategic planning in SMEs and to formulate some problem areas that need special attention and responsible action.SMEs; corporate strategic planning; information provision for strategic planning purposes.

Challenges with bearings only tracking for missile guidance systems and how to cope with them.

This paper addresses the problem of closed loop missile guidance using bearings and target angular extent information. Comparison is performed between particle filtering methods and derivative free methods. The extent information characterizes target size and we show how this can help compensate for observability problems. We demonstrate that exploiting angular extent information improves filter estimation accuracy. The performance of the filters has been studied over a testing scenario with a static target, with respect to accuracy, sensitivity to perturbations in initial conditions and in different seeker modes (active, passive and semi-active)

Dynamics of the Financial Wealth of the Institutional Sectors in Bulgaria: Empirical Studies of the Post-Communist Period

The question of who benefits and who loses from the transition, the channels and mechanisms of redistribution of wealth in the post-communist period, and the relation between redistribution and monetary regime are, in our opinion, fundamental in understanding theoretically the deep systemic changes in Eastern Europe. This article has two basic tasks – one empirical and one theoretical. Our empirical task is to analyse the dynamics of the financial wealth of the institutional sectors in Bulgaria in the period 1998-2005 and to identify the major net creditors and net debtors. The empirical data used for the purpose are based on adapted methodology for the financial account of the Bulgarian economy according to the requirements of the System of National Accounts (SNA). Econometric simulations have been carried out of the major factors conditioning the change in the sectoral financial wealth. The empirical investigations are given in Part 3. Our theoretical task is to prove the hypothesis (which is to a large extent supported by the empirical results) about the functional relationship between the dynamics of redistribution and the change in monetary regime. This is presented in Part 2 and is discussed in Part 4.redistribution, financial wealth, financial account, Bulgaria

Structured Sparse Modelling with Hierarchical GP

In this paper a new Bayesian model for sparse linear regression with a spatio-temporal structure is proposed. It incorporates the structural assumptions based on a hierarchical Gaussian process prior for spike and slab coefficients. We design an inference algorithm based on Expectation Propagation and evaluate the model over the real data.Comment: SPARS 201

Video foreground detection based on symmetric alpha-stable mixture models.

Background subtraction (BS) is an efficient technique for detecting moving objects in video sequences. A simple BS process involves building a model of the background and extracting regions of the foreground (moving objects) with the assumptions that the camera remains stationary and there exist no movements in the background. These assumptions restrict the applicability of BS methods to real-time object detection in video. In this paper, we propose an extended cluster BS technique with a mixture of symmetric alpha stable (SS) distributions. An on-line self-adaptive mechanism is presented that allows automated estimation of the model parameters using the log moment method. Results over real video sequences from indoor and outdoor environments, with data from static and moving video cameras are presented. The SS mixture model is shown to improve the detection performance compared with a cluster BS method using a Gaussian mixture model and the method of Li et al. [11]

Particle approximations of the score and observed information matrix for parameter estimation in state space models with linear computational cost

Poyiadjis et al. (2011) show how particle methods can be used to estimate both the score and the observed information matrix for state space models. These methods either suffer from a computational cost that is quadratic in the number of particles, or produce estimates whose variance increases quadratically with the amount of data. This paper introduces an alternative approach for estimating these terms at a computational cost that is linear in the number of particles. The method is derived using a combination of kernel density estimation, to avoid the particle degeneracy that causes the quadratically increasing variance, and Rao-Blackwellisation. Crucially, we show the method is robust to the choice of bandwidth within the kernel density estimation, as it has good asymptotic properties regardless of this choice. Our estimates of the score and observed information matrix can be used within both online and batch procedures for estimating parameters for state space models. Empirical results show improved parameter estimates compared to existing methods at a significantly reduced computational cost. Supplementary materials including code are available.Comment: Accepted to Journal of Computational and Graphical Statistic

A Box Particle Filter for Stochastic and Set-theoretic Measurements with Association Uncertainty

This work develops a novel estimation approach for nonlinear dynamic stochastic systems by combining the sequential Monte Carlo method with interval analysis. Unlike the common pointwise measurements, the proposed solution is for problems with interval measurements with association uncertainty. The optimal theoretical solution can be formulated in the framework of random set theory as the Bernoulli filter for interval measurements. The straightforward particle filter implementation of the Bernoulli filter typically requires a huge number of particles since the posterior probability density function occupies a significant portion of the state space. In order to reduce the number of particles, without necessarily sacrificing estimation accuracy, the paper investigates an implementation based on box particles. A box particle occupies a small and controllable rectangular region of non-zero volume in the target state space. The numerical results demonstrate that the filter performs remarkably well: both target state and target presence are estimated reliably using a very small number of box particles