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The purpose of this paper is to measure the financial risk and optimal capital structure of a corporation.

Irregular disjunctive programming problems arising in firm models and risk management can be solved by the techniques presented in the paper.

Parallel processing and mathematical modeling provide a fruitful basis for solving ultra-scale non-convex general disjunctive programming (GDP) problems, where the computational challenge in direct mixed-integer non-linear programming (MINLP) formulations or single processor algorithms would be insurmountable.

The test is limited to a single firm in an experimental setting. Repeating the test on large sample of firms in future research will indicate the general validity of Monte-Carlo-based VAR estimation.

The authors show that the risk surface of the firm can be approximated by integrated use of accounting logic, corporate finance, mathematical programming, stochastic simulation and parallel processing.

Parallel processing has potential to simplify large-scale MINLP and GDP problems with non-convex, multi-modal and discontinuous parameter generating functions and to solve them faster and more reliably than conventional approaches on single processors.

The purpose of this article is to provide an overview about the Semantic Web, its importance and history and an overview of recent Semantic Web technologies which can be used to enhance digital libraries.

The paper answers, at least partially, questions like “What is the Semantic Web?”, “How could the Semantic Web look like?”, “Why is the Semantic Web important?”, “What are ontologies?” and “Where are we now?”. Several pointers to further literature and web sites complete the overview.

Semantic Web technologies are valuable add‐ons for digital libraries. There already exist numerous academic and commercial tools which can be applied right now.

The overview of Semantic Web technologies cannot be complete in such an article, therefore we limit ourselves to the most prominent technologies available. However, following the pointers given readers can easily find more information.

The article is of particular value for newcomers in this area.

In the vast majority of the individual robot installations, the robot arm is just one piece of a complex puzzle of components, such as grippers, jigs or external axis, that together compose an industrial robotic cell. The success of such installations is very dependent not only on the selection of such components but also on the layout and design of the final robotic cell, which are the main tasks of the system integrators. Consequently, successful robot installations are often empirical tasks owing to the high number of experimental combinations that could lead to exhaustive and time-consuming testing approaches.

A newly developed optimized technique to deal with automatic planning and design of robotic systems is proposed and tested in this paper.

The application of a genetic-based algorithm achieved optimal results in short time frames and improved the design of robotic work cells. Here, the authors show that a multi-layer optimization approach, which can be validated using a robotic tool, is able to help with the design of robotic systems.

The usage of the proposed approach can be valuable to industrial corporations, as it allows for improved workflows, maximization of available robotic operations and improvement of efficiency.

To date, robotic solutions lack flexibility to cope with the demanding industrial environments. The results presented here formalize a new flexible and modular approach, which can provide optimal solutions throughout the different stages of design and execution control of any work cell.

The purpose of this research is to describe a system to support querying across distributed digital libraries created in heterogeneous metadata schemas, without requiring the availability of a global schema.

The advantages and weaknesses of ontology based applications were investigated and have justified the utility of inferential rules in expressing complex relations between metadata terms in different metadata schemas. A process for combining ontologies and rules for specifying complex relations between metadata schemas were designed. The process was collapsed into a set of working phases and provides examples to illustrate how to interrelate two similar bibliographic ontology fragments for further query reformulation.

Equipping ontologies with inferencing power can help describe more complex relations between metadata terms. This approach is critical for properly interpreting queries from one ontology to another.

A prototype system was built based on examples instead of practical experience.

The approach assumes that relations between metadata sets, or ontologies in the approach, are provided by domain experts with/without ontology tools.

A new approach has been proposed for facilitating heterogeneous metadata interoperation in digital libraries as a way of empowering ontologies with rich reasoning capabilities. The traditional approach assumes a global schema controlled by a central or virtual server to provide mapping between local and external metadata schemas. A more flexible and dynamic environment was studied, i.e. P2P‐based digital libraries, where peers may join and leave freely.

The disjunctive graph is a network representation of the job‐shop scheduling problem, while the longest path problem (LPP) is one of the most important subjects in this research field. This paper aims to study the special topological structure of the disjunctive graph, and proposes a suite of quick value‐setting algorithms for solving the LPPs commonly encountered in job‐shop scheduling.

The topological structure of the disjunctive graph is analyzed, and some properties and propositions regarding LPPs are presented. Subsequently, algorithms are proposed for solving LPPs encountered in job‐shop scheduling.

The proposed algorithms significantly improve the efficiency of the shifting‐bottleneck procedure, making it practicable to realise real‐time scheduling and hence effective operations of modern manufacturing systems.

The paper demonstrates that it is possible to develop very efficient algorithms by imposing a special topological structure on the network.

Bibliometrics is one of the research fields in library and information science that deals with the analysis of academic entities. In this regard, to gauge the productivity and popularity of authors, publication counts and citation counts are common bibliometric measures. Similarly, the significance of a journal is measured using another bibliometric measure, impact factor. However, scarce attention has been paid to find the impact and productivity of conferences using these bibliometric measures. Moreover, the application of the existing techniques rarely finds the impact of conferences in a distinctive manner. The purpose of this paper is to propose and compare the DS-index with existing bibliometric indices, such as h-index, g-index and R-index, to study and rank conferences distinctively based on their significance.

The DS-index is applied to the self-developed large DBLP data set having publication data over 50 years covering more than 10,000 conferences.

The empirical results of the proposed index are compared with the existing indices using the standard performance evaluation measures. The results confirm that the DS-index performs better than other indices in ranking the conferences in a distinctive manner.

Scarce attention is paid to rank conferences in distinctive manner using bibliometric measures. In addition, exploiting the DS-index to assign unique ranks to the different conferences makes this research work novel.

The content, provided in learning management systems (LMS), is often text oriented as in a usual textbook, extended by some animations and links. Hands on activities and experiments are not possible. The paper aims to give an overview about the concept to couple smart simulation and assessment tools with an LMS to provide a more explorative approach to the learning content.

Interactive components, such as smart design tools and online laboratories are added to an LMS that allow exploring the learned content additionally to text parts interactively. The objective of this teaching concept is to empower the students to solve complex design tasks for digital systems and to validate the results. This requires on the one hand site knowledge about the mathematical background of the algorithms used by design tools, and on the other hand, experience from as much as possible examples. Commercial tools are too complex for teaching purposes and hide mostly the algorithms they use for the several design steps. That is why we have developed smart special tailored tools for each single design step that should be learned during a lesson.

These smart tools are very useful to support the process of understanding and learning by doing. Learners can explore the several design steps with own examples and get immediately feedback about the correct solutions.

The connection to an LMS allows us to record all students' relevant actions in the design process and to evaluate the student or to give individual tailored hints.

The paper introduces a new teaching concept that allows exploring the learned content interactively additionally to text parts.

Scheduling is defined by Baker as, “the allocation of resources over time to perform a collection of tasks”. The term facilities is often used instead of resources and the tasks to be performed may involve a variety of different operations.

The OTS/CafeOBJ method can be used to formally model, specify and verify distributed systems such as security protocols and railroad systems. A distributed system is modeled as an OTS, a kind of transition system, and the OTS is specified and verified with CafeOBJ, an algebraic specification language. Case analysis (or case splitting) is one of the most intellectual pieces of work in verification. Case analysis should be done entirely by hand in the OTS/CafeOBJ method, which is errorprone. It is indispensable to cover all cases and find necessary lemmas for some sub‐cases where desired results are not obtained in case analysis. We propose two methods of mechanically supporting case analysis, which concern these two issues. A case study that the proposed methods are effectively applied to a railroad signaling system is also reported.

A general theory of conceptual systems (GCST) is developed, in which the concept of systems is introduced not a priori or theoretically, but by means of a rigorous procedure, supported by experimental knowledge of these or other system realization forms (so‐called “realization” and “trajectories”). This is the stage of an inductive construction of computable concepts, i.e. “concepts”. “Concept” is presented in the form of a function of discrete variables, one part of which is known (essential variables), while the other part is independent (non‐essential variables). The presence of “concept” allows one to construct new, not yet realized “trajectories”. This is the stage of the deductive conclusion. The general principles of GCST construction on the basis of an artificial intelligence program system are formulated. This approach excludes widespread methods of a priori construction of system theories (e.g. in the “theory of usefulness”, the “study of operations”).