The paper deals with coalitions whose members are unselfish. Coalition members do their best to completethe arising tasks, and do not expect to receive a reward. A coalition member can be an entity such as a social orgovernmental organization, a military unit, or a complex technical device such as an autonomous robot, or any otherentity that has the capabilities, willingness, and ability to cooperate. The paper considers the non-redundant coalitions,which have only those coalition members without whom they cannot perform the tasks. In the paper, we consider onlythe situations when substitution of failed coalition members is impossible. A coalition tolerates the failure of itsmembers by using the surplus of coalition capabilities. In our research, coalition capabilities are understood as resourcesand services (e.g., materials, energy, power etc.). During the execution of tasks, one or more members of the coalitionmay fail. The paper uses the probability of the event that the coalition tolerates the failures of its members to evaluatethe coalition fault tolerance. A method is proposed for determining the coalition fault tolerance in the case of multiplemember failures. Complexity of the proposed method and its applicability are assessed.

System-level self-diagnosis is one of the most important tasks in the field of computer science. In this paper, we present the results of the research on how to increase the credibility of the results of system diagnosis by way of merging two methods of system-level self-diagnostic (traditional and unconventional). As distinct from traditional system level self-diagnosis, unconventional method of system diagnosis can deal with arbitrary testing assignments and can be applied to heterogeneous systems. The diagnosis problem consists of determining the location of faults in the system (i.e., determining faulty units). In traditional system level self-diagnosis, such diagnosis problem can be defined as finding the necessary and sufficient conditions for a system testing assignment that should be satisfied to achieve a given level of diagnosability given a fault model and an allowable family of fault sets. For solving the diagnosis problem the appropriate diagnosis algorithms should be developed. Before designing a diagnosis algorithm it is needed to adopt the strategy that is suitable for the particular complex system. Among the possible diagnosis strategies, such as unique, sequential, excess and probabilistic, the probabilistic strategy was chosen. Based on this strategy, the diagnosis algorithms were designed. The results (credibility) of the algorithms that follow the probabilistic diagnosis strategy can be improved. For this purpose, some elements of unconventional system level self-diagnosis are used in the algorithm design. Short description of unconventional system level self-diagnosis is presented in this paper. The obtained results of improved diagnosis allow revealing the functional dependence of the credibility of diagnosis results on the values of system and testing parameters.

The paper tackles the problem of performing mutual testing in complex systems. It is assumed that units of complex systems can execute tests on each other. Tests among system units are part of system diagnosis that can be carried out both before and during system operation. The paper considers the case when tests are executed during system operation. Modelling and simulating mutual tests will allow evaluation of the efficiency of using joint testing in the system. In the paper, the models that use Petri Nets were considered. These models were used for simulating the execution of tests among system units. Two methods for performing such simulations were evaluated and compared. Recommendations for choosing a more appropriate way were made. Simulation results have revealed minor model deficiencies and possible implementation of mutual testing in complex systems. Improvement of the model was suggested and assessed. A recommendation for increasing the efficiency of system diagnosis based on joint testing was made.

The paper deals with alliances and coalitions that can be formed by agents or entities. It is assumed that alliance agents cooperate and form coalitions for performing the tasks or missions. It is considered that alliance agents are unselfish. That is, they are more interested in achieving the common goal(s) than in getting personal benefits. In the paper, the concept of fuzzy alliance was introduced. A fuzzy alliance is considered as generalization of traditional alliance allowing agents to decide on the capabilities that their agents can and wanted deliver to coalition. Coalitions that can be formed by fuzzy alliance agents were considered. The definition of the “best” coalition was explained. The method of how to find the “best” coalition among all possible coalitions was suggested and verified by computer simulation.

Scientific research is devoted to determining the areas of integrated application of the formal method Event-B for the development of environmental management systems. The practice of prevention and elimination of environmental emergencies indicates the general nature of risks in the field of environmental, industrial and occupational safety. Accordingly, the management of these risks is optimally carried out on a single basis - in the framework of the creation of environmental management systems (objects of management are considered man-made hazardous objects, ecosystem objects). The application of the method of formal verification of Model Checking and the method of specification of requirements of Event-B at synthesis of administrative ecological decisions is offered. The formalization of management decisions in the system of ecological management in the conditions of abnormal ecological situations is given.

The paper reveals the problem of the lack of standard non-destructive diagnostic methods for high-power microwave devices aimed at regeneration.The issue is understudied and requires further research.The conducted analysis of state of the art on the subject area exhibited that image processing was used to specify the examined object's target characteristics in a wide range of research.Having summarized the considered image comparison methods on the subject area of this work, the authors formulated several requirements for the selected image analysis method based on the automated non-destructive diagnosis of resonator units for high-power magnetrons.The primary requirement is using non-iterative algorithms; the second condition is a chosen method of image analysis, and the third option is the number of pixels for a processed image.It must significantly exceed the number of descriptors required for making a decision.Guided by the analysis results and based on the results of previous studies conducted by the authors, the algorithm for identifying a defect in the resonator unit of a microwave device based on the image of the frequencyazimuthal distribution for the probing field phase difference expressed by the Zernike moments is proposed.MATLAB R14a was used as a modeling environment.The descriptor vector was restricted to the Zernike moments, including the 7th order.The work is interdisciplinary and written at the intersection of technical diagnostics, microwave engineering, and digital image processing.

This research suggests unconventional approach to system level self-diagnosis. Self-diagnosis at the system level has traditionally centred on determining the state of the units that are tested by other system units. The suggested approach, on the other hand, relies on the results of tests done by a system unit to determine its own condition. Since a unit examines its own status, which is fundamental in self-testing, such diagnosis is similar to self-testing in many ways. In contrast to self-testing, the proposed approach has a unit evaluate itself based on tests performed on other system units rather than on itself. Different diagnosis models with varied testing assignments and different faulty assumptions, such as permanent and intermittent faults, as well as hybrid-fault situations, are investigated. The diagnosis algorithm for determining the state of the unit has been devised, and its validity has been verified by computer simulation. Conventionally, for self-testing and self-diagnosis it is implicitly assumed that a unit includes some fault-free subsystem capable of executing the diagnosis algorithms correctly.

The methods for calculating the failures risks of the high-temperature pressurized pipelines are developed as the particulars of the generalized approaches for the risk assessment in stationary deterministic systems. It is considered the straight pipe as the necessary required part of pipelines, and it is proposed considering it under the internal and external pressures for the given temperature. The pipe's failures risks are measured by the gamma-percentile life. It is proposed the mathematical model representing the deterministic properties of the high-temperature pressurized pipe needed for calculating their failures risks. In this mathematical model it is took into account accumulating the irreversible strains and damages in the pipe's during operating due to the high-temperature creep, and this mathematical model is represented as the theory of creep initial-boundary-value problem and numerical solving of such problems is briefly discussed. It is proposed the general approximation of the high-temperature pressurized pipe's life depending on the internal and external operating pressures. It is considered the particular example of the high-temperature pressurized pipe made from the stainless austenitic steel, and its gamma-percentile life is computed. It is shown that the gamma-percentile life is the failures risks quantitative measure which really gives the most fully and correct characteristic of the failures risks for the high-temperature pressurized pipes during their operating, because the gamma-percentile life of the pipe is very sensitive to the value of required probability of operating without the failures.

The paper considers the transition from traditional methods and systems for determining the standard and limit states of potentially dangerous objects by criteria of strength, resource and reliability to new perspective methods for assessing the risks of managing them. The conditions for ensuring the complex safety and security of the equipment and high-risk structures by the criteria of acceptable and managed risks are determined. It is established that the level of risk for assessing the safety status of a potentially dangerous object is defined as a probabilistic measure of the occurrence of man-made or natural phenomena, which are accompanied by the formation and action of harmful factors, as well as inflicted social, environmental, economic and other kinds of losses.

Unit self-diagnosis is considered at system level. As distinct from system level self-diagnosis based on units mutual tests, we have researched the method based on the tests which a unit performs on other system units. Taking into account the obtained test results, a unit evaluates its own state. In our research, we have considered different faulty assumptions and testing procedures. Diagnosis model was developed and analyzed. Computer simulation is performed by using the web application developed for this research. Results of simulation were analyzed and assessed. Some recommendations were made for achieving better diagnosis results.

This paper suggests unconventional approach to system level self-diagnosis.Traditionally, system level self-diagnosis focuses on determining the state of the units which are tested by other system units.In contrast, the suggested approach utilizes the results of tests performed by a system unit to determine its own state.Such diagnosis is in many respects close to self-testing, since a unit evaluates its own state, which is inherent in selftesting.However, as distinct from self-testing, in the suggested approach a unit evaluates it on the basis of tests that it does not performs on itself, but on other system units.The paper considers different diagnosis models with various testing assignments and different faulty assumptions including permanent and intermittent faults, and hybrid-fault situations.The diagnosis algorithm for identifying the unit's state has been developed, and correctness of the algorithm has been verified by computer simulation experiments.

Mostly, diagnosis at a system level intends to identify only permanently faulty units. In the paper, we consider the case when both permanently and intermittently faulty units can occur in the system. Identification of intermittently faulty units has some specifics which we have considered in this paper. We also suggest the method which allows for distinguishing among different types of intermittent faults. A diagnosis procedure was suggested for each type of intermittent fault.

System level diagnosis is an abstraction of high level and, thus, its practical implementation to particular cases of complex systems is the task which requires additional investigations, both theoretical and modeling. Mostly, diagnosis at system level intends to identify only permanently faulty units. In the paper, we consider the case when both permanently and intermittently faulty units can occur in the system. Identification of intermittently faulty units has some specifics which we have considered in this paper. We also suggest the method which allows distinguishing among different types of intermittent faults. Diagnosis procedure was suggested for each type of intermittent faults.

System level diagnosis is an abstraction of high level and, thus, its practical implementation to particular cases of complex systems is the task which requires additional investigations, both theoretical and modeling. Traditionally, system self-diagnosis is used for detecting of permanently faulty nodes. In the paper, we consider the problems of intermittent fault detection and suggest diagnosis procedures which allow distinguishing between different types of intermittent faults. For each type of intermittent faults the diagnosis procedure was developed

The paper deals with the problem of system level self-diagnosis. Usually it is assumed that a system unit is tested when it is idle and, thus. it can participate in a test. It means that a system unit cannot be tested continuously. In view of this, there is a probability of system unit fault omission. In the paper, we show how the tests of the system units are organized and proposed the method of evaluating the credibility of the results of system checking.

In the paper, formation of coalitions with the agents of an alliance is considered. It is assumed that the agents of an alliance can negotiate with each other, form coalitions and interact eventually. Only not self-interested agents are considered. Nevertheless, the agents may have their own strategies while choosing the partners for negotiations. It is also assumed that some of the agents may refuse to cooperate with some other agents of the same alliance. Coalition formation is a complex process which has many probabilistically defined parameters. Therefore, it is difficult to determine which coalition will be formed and how long it will last. To solve the coalition formation task effectively, appropriate modeling is commonly used. In the paper, it is shown how Stochastic Petri Nets can be applied to coalition formation modeling. Simulation was performed by using the devised coalition formation model, and the obtained results were analyzed.

The paper concerns system level self-diagnosis (SLSD). SLSD aims at diagnosing systems composed by units with the requirement that they are able to test each other by exchanging information through available links. At this level of diagnosis, each particular test is considered as atomic. It means that the details of a test are abstracted (not considered), and only the result of test is taken into consideration. One of the main issues of SLSD is the issue of testing assignment that defines the possible set of tests among the system units. System testing assignment relies and depends on physical connections among the system units. The issue of testing assignment is tightly connected with the diagnosability problem of SLSD. Diagnosability problem of SLSD is the problem of how to determine the family of fault sets that a given testing assignment can diagnose for some fault model. In the paper, we have shown how different testing assignments can be evaluated and compared. For this, we suggest to use characteristic numbers. We also have shown how these characteristic numbers can be computed.

One of the challenges of agent technologies is to provide models of team or group activities in which agents contact each other, negotiate and collaborate towards certain objectives. Such groups are related to multi-agent systems. In context of multi-agent systems, separate agents can cooperate and join together in order to execute the faced tasks in a more efficient way or in order to gain benefits. The paper deals with unselfish agents which are concerned about the system’s global outcome, without regards for personal payoff. Coalition formation is a very complex process which requires correct planning and preliminary modeling to be solved effectively. In the paper, we considered the problem of modeling the coalition formation from unselfish agents. There are several tools that allow providing and carrying out coalition formation modeling. In the paper, we showed how the Petri Nets can be used for such modeling. For the purpose of simulation of coalition formation the open access web application was developed.

The paper represents the analysis of the main issues of system level self-diagnosis and explanation of its three basic problems.The main attention is paid to the problem of diagnosis which is expressed with the help of set theory.The influence of made assumptions concerning the allowable faulty sets on the diagnosis results is discussed with the help of simple example.