The meta-heuristic called Co-Operation of Biology Related Algorithms (COBRA) developed earlier for solving real-valued optimization problems has also been modified for solving optimization problems with binary variables (COBRA-b). The algorithm COBRA-b is based on a collective work of five nature-inspired algorithms' binary modifications such as Particle Swarm Optimization (PSO), the Wolf Pack Search Algorithm (WPS), the Firefly Algorithm (FFA), the Cuckoo Search Algorithm (CSA) and Bat Algorithm (BA). Its usefulness and workability were demonstrated on various benchmarks, and COBRA-b also outperformed its components. But solving problems sometimes required too many function evaluations, so the COBRA-b migration operator was modified by integrating biogeography principles for the speedup of the algorithm. Numerical experiments showed that the new modification exhibits high performance and outperforms COBRA-b and therefore its components.

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Speech analysis nowadays is widespread. One of its applications is designing Spoken Dialogue Systems, which allow users to interact with computer systems using natural spoken language. The Interaction Quality is a quality metric, which is used in this field to evaluate the quality of interaction between computer and human. It is based on various speech features. The aim of the Interaction Quality model design is to improve Spoken Dialogue Systems by introducing information about Interaction Quality into Spoken Dialogue Modeling. There exists some state-of-the-art related to the Interaction Quality in spoken human-computer communication. In turn, measuring the Interaction Quality for humanhuman conversation reveals to be an increasingly difficult task. Different types of dialogue exist and for each type the Interaction Quality measure has a different meaning. Furthermore, a specific data corpus is required for modeling the Interaction Quality for each type of dialogue. We describe the idea of developing software tool for semi-automatic dialogue corpus generation, which can help to keep the time for preparing corpora. The Interaction Quality models for human-human conversations can be used for improving Spoken Dialogue Systems in terms of flexibility, human-likeness and user-friendliness. What is more, the results of the Interaction Quality modeling can be useful in the field of manned space exploration for developing systems for automatic monitoring the conditions of the crew of a spaceship, especially for long interplanetary flights. Further development of the work on the Interaction Quality modeling will help to track automatically relationship between crew members on the basis of their speech.

This paper describes the problem of human resource management which can appear in many organizations during restructuration periods. The problem is simulated by a dynamic model, similar to a supply chain model with several ranks. The problem of finding the optimal combination of transition coefficients, including the fluctuation coefficients, is transformed into an optimization problem. To solve this problem, a self-configuring genetic algorithm is applied with several constraint handling methods. Additional constraints are defined in order to avoid undesirable oscillations in the system. The results show that this problem can be efficiently solved by the presented methods.

Various data mining techniques are designed for extracting significant and valuable patterns from huge databases. Today databases are often divided between several organizations for the reason of limitations like geographical remoteness, but the most important limit is preserving privacy, unwillingness of data disclosing. Every party involved in analysis wants to keep its own information private because of legal regulations and reasons of know-how. Secure multiparty computations are designed for data mining execution in a multiparty environment, where it is extremely important to maintain the privacy of the input (and possibly output) data. A self-organizing map is the data mining method by which analytics can display patterns on two-dimensional intuitive maps and recognize data clusters. This article presents protocols for preserving privacy in the process of building self-organizing maps. The protocols allow the implementation of a self-organizing map algorithm for two parties with horizontally partitioned data and for several parties with vertically partitioned data.