Hierarchical Systems

In this paper, the problem of optimal choice of sensors and actuators is addressed. Given a functional encapsulating information of the desired performance and production economy the objective is to choose a control instrumentation from a given set to comply with its minimum. The objective of the work is twofold: reformulation of the business objectives into mathematical terms and providing solution to the given optimization. Commonly, there exist overall business objectives which dictate how a plant should be instrumented and operated either directly or indirectly. The work shows how to propagate a global objective to local subsystems. Particular focus is on a boiler in a power plant operated by DONG Energy -a danish energy supplier. The business objectives have been propagated to the actuator level to allow for selection of an actuator configuration.

Computational Grid (CG) provides a wide distributed platform for high end compute intensive applications. Inter Process Communication (IPC) affects the performance of a scheduling algorithm drastically. Genetic Algorithms (GA), a search procedure based on the evolutionary computation, is able to solve a class of complex optimization problems. This paper proposes a GA based scheduling model observing the effect of IPC on the performance of scheduling in computational grid. The proposed model studies the effects of Inter Process Communication (IPC), processing rate ( m ) and arrival rate ( l ). Simulation experiment, to evaluate the performance of the proposed algorithm is conducted and results reveal the effectiveness of the model.

Grid is a parallel and distributed computing network system comprising of heterogeneous computing resources spread over multiple administrative domains that offers high throughput computing. Since the Grid operates at a large scale, there is always a possibility of failure ranging from hardware to software. The penalty paid of these failures may be on a very large scale. System needs to be tolerant to various possible failures which, in spite of many precautions, are bound to happen. Replication is a strategy often used to introduce fault tolerance in the system to ensure successful execution of the job, even when some of the computational resources fail. Though replication incurs a heavy cost, a selective degree of replication can offer a good compromise between the performance and the cost. This chapter proposes a co-scheduler that can be integrated with main scheduler for the execution of the jobs submitted to computational Grid. The main scheduler may have any performance optimization criteria; the integration of co-scheduler will be an added advantage towards fault tolerance. The chapter evaluates the performance of the co-scheduler with the main scheduler designed to minimize the turnaround time of a modular job by introducing module replication to counter the effects of node failures in a Grid. Simulation study reveals that the model works well under various conditions resulting in a graceful degradation of the scheduler's performance with improving the overall reliability offered to the job.

Computational Grid (CG) provides a wide distributed platform for high end compute intensive applications. Inter Process Communication (IPC) affects the performance of a scheduling algorithm drastically. Genetic Algorithms (GA), a search procedure based on the evolutionary computation, is able to solve a class of complex optimization problems. This paper proposes a GA based scheduling model observing the effect of IPC on the performance of scheduling in computational grid. The proposed model studies the effects of Inter Process Communication (IPC), processing rate () and arrival rate (). Simulation experiment, to evaluate the performance of the proposed algorithm is conducted and results reveal the effectiveness of the model.

Grid supports heterogeneities of resources in terms of security and computational power. Applications with stringent security requirement introduce challenging concerns when executed on the grid resources. Though grid scheduler considers the computational heterogeneity while making scheduling decisions, little is done to address their security heterogeneity. This work proposes a security aware computational grid scheduling model, which schedules the tasks taking into account both kinds of heterogeneities. The approach is known as Security Prioritized MinMin (SPMinMin). Comparing it with one of the widely used grid scheduling algorithm, MinMin (secured) shows that SPMinMin performs better and sometimes behaves similar to MinMin under all possible situations in terms of makespan and system utilization.

This paper presents a grid scheduling model to schedule a job on the grid with the objective of ensuring maximum reliability to the job under the current grid state. The model schedules a modular job to those resources that suit the job requirements in terms of resources while offering the most reliable environment. The reliability estimates depict true grid picture and considers the contribution of the computational resources, network links and the application awaiting allocation. The scheduling executes the interactive jobs while considering the looping structure. As scheduling on the grid is an NP hard problem, soft computing tools are often applied. This paper applies Modified Genetic Algorithm (MGA), which is an elitist selection method based on the two threshold values, to improve the solution. The MGA works on the basis of partitioning the current population in three categories: the fittest chromosomes, average fit chromosomes and the ones with worst fitness. The worst are dr...

Computational Grid attributed with distributed load sharing has evolved as a platform to large scale problem solving. Grid is a collection of heterogeneous resources, offering services of varying natures, in which jobs are submitted to any of the participating nodes. Scheduling these jobs in such a complex and dynamic environment has many challenges. Reliability analysis of the grid gains paramount importance because grid involves a large number of resources which may fail anytime, making it unreliable. These failures result in wastage of both computational power and money on the scarce grid resources. It is normally desired that the job should be scheduled in an environment that ensures maximum reliability to the job execution. This work presents a reliability based scheduling model for the jobs on the computational grid. The model considers the failure rate of both the software and hardware grid constituents like application demanding execution, nodes executing the job, and the ne...

One of the application areas of genetic algorithms is parameter optimization. This paper addresses the problem of optimizing a set of parameters that represent the weights of criteria, where the sum of all weights is 1. A chromosome represents the values of the weights, possibly along with some cut-off points. A new crossover operation, called continuous uniform crossover, is proposed, such that it produces valid chromosomes given that the parent chromosomes are valid. The new crossover technique is applied to the problem of multicriteria inventory classification. The results are compared with the classical inventory classification technique using the Analytical Hierarchy Process. @ 1998 Elsevier Science B.V.

This paper conducts a comprehensive exploration of the methodology in historical linguistics, focusing on language subgrouping. Employing Tangut, a severely eroded mediaeval language, as a case study, it scrutinises previous linguistic analyses that depart from the rigorous Neogrammarian method, specifically referencing Beaudouin (2023). These non-compliant analyses have impeded recent progress in understanding the genetic relationships within Burmo-Qiangic, a field marked by prolonged debates and with gradual advancement recently. In a subsequent step, adhering to Neogrammarian principles, namely, Ausnahmslosigkeit der Lautgesetze and positive shared innovations in language subgrouping, the paper discusses the plausibility of, as well as the good practice to argue for a "Tangut-Horpa clade" within the Gyalrongic branch of Burmo-Qiangic. By advocating for the universality of these Neogrammarian principles, the paper aims to improve the accuracy and reliability of subgrouping languages characterised by significant typological diversity. This, in turn, contributes to a deeper comprehension of rigorous methodology within the context of the Sino-Tibetan language family.

In this paper we present a novel method for gesture video decomposition based on the depicted content. From the initial content the key-frames are extracted and the neighboring frames are assigned to key-frames of similar content. The resulting frame groups are decomposed to binary trees, based on the energy of the depicted gestures. In case of reduced bandwidth we keep the original timeline but we send only a dynamically adapted video summary. The respective frames are obtained by moving appropriately across the hierarchy layers of the constructed tree. The hierarchically structured video can be used for purposes such as efficient video browsing and transmission of dynamically generated summaries over low bandwidth networks, for communication or human-computer interface applications. I

Contribuții la Filosofie și Știință prin Logica Contradicțiilor Stéphane Lupasco (1900-1988) a fost un filozof franco-român cunoscut pentru teoria sa despre logica dinamică a contradictoriului. El a propus o logică non-aristotelică în care contradicția nu este eliminată, ci gestionată într-un mod dinamic, inspirat de principiile mecanicii cuantice. Principalele idei ale lui Lupasco I. Ternarul logic-Spre deosebire de logica clasică binară (adevărat/fals), Lupasco a introdus un al treilea termen: starea de potențialitate. Aceasta indică faptul că un fenomen nu este complet determinat, ci poate oscila între două stări contradictorii. În logica clasică aristotelică, un enunț este fie adevărat, fie fals, fără posibilități intermediare. Această abordare este fundamentală pentru gândirea rațională tradițională, însă Lupasco a propus o logică dinamică, în care realitatea nu este fixă, ci un proces continuu de transformare.

A Historical-philosophical Sketch of the Beginnings of Strict Finitism. The aim of our paper is to offer a historical sketch of the beginnings of strict finitism, especially from the point of view of its many philosophical aspects. A major hypothesis of our approach is that this presentation could be better done if we have in mind as a necessary background the intuitionistic, and broadly speaking constructivist mathematical issues, also in a historical dimension. As a result, apart from some brief general remarks, we will give here an insight mainly into the texts of some pioneering works in this field of Paul Bernays, Émile Borel and David van Dantzig and into some important connections with Brouwer's intuitionism.

This paper aims to provide a combinatory approach towards addressing the advanced ATP problem, consisting of three deterministic optimization models that operate on both sides of the Customer Order Decoupling Point. The proposed approach is based on long term aggregate capacity reservation for periods when increased volatility is expected, while still obtaining production plans that meet the predefined and agreed customer service levels. The three optimization models together guide a system that helps manufacturers to optimally decide on ATP quantity and due date quoting on the basis of available manufacturing resources. To support this system, a prototype software module was designed and implemented in Java that loosely integrates with the popular Open Source ERP system Compiere2's databases and uses the Linear Programming solver QS-Opt to solve the models developed in this research. The system response times as evidenced in the experiments described in this paper are quite acceptable for real-world operations. The proposed solution of the ATP problem is of great value for all competitive and proactive organizations that need a practical tool to support, in the best possible way and in an almost real time fashion, their decision on whether to accept or decline an incoming customer order request. It is our belief that an integration of the proposed models into existing ERP systems will enhance their limited ATP functionality and provide management with a powerful decision support tool.

The simulation of large scale nonlinear dynamical interconnected systems, as they arise in all modern engineering disciplines, is a usual task. Due to the high complexity of the considered systems, the principle of thinking in hierarchical structures is essential and common among engineers. Therefore, this contribution proposes an approach for the numerical simulation of large systems, which keeps the hierarchical system structure alive during the entire simulation process while simultaneously exploiting it for order reduction purposes. This is accomplished by embedding the trajectory piecewise linear order reduction scheme in a modified variant of the component connection modeling for building interconnected system structures. The application of this concept is demonstrated by means of a widely used benchmark example and a modified variant of it.

This study develops a new Sensor Fault-Tolerant methodology for two-level Centralized Hierarchical Control of isolated microgrids based on a modified Kalman filter algorithm. The main objective is to increase the reliability and safety margins of isolated smart microgrids in the presence of different sensor faults on the secondary control. Consequently, Sensor Fault-Tolerant control reduces the costs because costly redundant hardware is not required. Because of its low computing effort, speed, ease of implementation, and tuning, this method can be used in more complex control configurations, multiple sensor faults, and different hierarchical control levels. The designed Sensor Fault-Tolerant Hierarchical Control System was initially proposed for a grid-forming topology of single-phase BESSs systems connected in cascade to the microgrid. The implemented fault tolerance methodology can maintain control objectives with sensor faults. Consequently, the MG's voltage at the time of the fault does not exceed 5%, and the voltage unbalance at the common coupling point or on the critical bus is compensated to a quality reference value of less than 2%. The performance of the proposed algorithm is tested using the MATLAB/Simulink simulation platform. INDEX TERMS Fault diagnosis, fault tolerant control, hierarchical system, microgrids, resilience.

One of the application areas of genetic algorithms is parameter optimization. This paper addresses the problem of optimizing a set of parameters that represent the weights of criteria, where the sum of all weights is 1. A chromosome represents the values of the weights, possibly along with some cutoff points. A new crossover operation, called continuous uniform crossover, is proposed, such that it produces valid chromosomes given that the parent chromosomes are valid. The new crossover technique is applied to the problem of multicriteria inventory classification. The results are compared with the classical inventory classification technique using the Analytical Hierarchy Process. @ 1998 Elsevier Science B.V.

In this paper the strategy profiles that are the Pareto-optimal Nash equilibriums are considered. Sufficient conditions for existence of the equilibrium for the pure strategies are found. These conditions use the Germier convolutions of the utility functions. For example, Pareto-optimal Nash equilibrium in Bryant games is constructed.

Orthogonalization is one of few mathematical methods conforming to mathematical standards for approximation. Finding a consistent PC matrix of a given an inconsistent PC matrix is the main goal of a pairwise comparisons method. We introduce an orthogonalization for pairwise comparisons matrix based on a generalized Frobenius inner matrix product. The proposed theory is supported by numerous examples and visualizations.

We study a P2P proactive search mechanism based on the dissemination of advertisements for the new sources. The system design goal of limiting the state maintained by each peer and ensuring search efficiency is the driving reason for exploiting the hierarchical network model of the small-world idea. The results testify the theoretical bounds on search time and provide a view on the search time in relation to the directory capacity requirements of the peers.

We introduce HHL, a hierarchical variant of hybrid logic. We study first order correspondence results and prove a Hennessy-Milner like theorem relating (hierarchical) bisimulation and modal equivalence for HHL. Combining hierarchical transition structures with the ability to refer to specific states at different levels, this logic seems suitable to express and verify properties of hierarchical transition systems, a pervasive semantic structure in Computer Science.

Within the last 20 years, computer simulations of materials have evolved from an academic curiosity to a predictive tool for addressing structure-property-processing-performance relations that are critical to the design of new products and processes. Chemical engineers, with their problem-oriented thinking and their systems approach, have played a significant role in this development. The computational prediction of physical properties is particularly challenging for polymeric materials, because of the extremely broad spectra of length and time scales governing structure and molecular motion in these materials. This challenge can only be met through the development of hierarchical analysis and simulation strategies encompassing many interconnected levels, each level addressing phenomena over a specific window of time and length scales. In this paper we will briefly discuss the fundamental underpinnings and example applications of new methods and algorithms for the hierarchical modelling of polymers. Questions to be addressed include: How can one equilibrate atomistic models of long-chain polymer melts at all length scales and thereby predict thermodynamic and conformational properties reliably? How can one quantify the structure of entanglement networks present in these melts through topological analysis and relate it to rheological properties? Are there ways to predict the microphase-separated morphology and stress-strain behaviour of multicomponent block copolymer-based materials, such as pressure sensitive adhesives? Is it possible to anticipate changes in the barrier properties of glassy amorphous polymers used in packaging applications as a consequence of modifications in the chemical constitution of chains?

Perception-Action (P-A) learning is an approach to cognitive system building that seeks to reduce the complexity associated with conventional environment-representation/actionplanning approaches. Instead, actions are directly mapped onto the perceptual transitions that they bring about, eliminating the need for intermediate representation and significantly reducing training requirements. We here set out a very general learning framework for cognitive systems in which online learning of the P-A mapping may be conducted within a symbolic processing context, so that complex contextual reasoning can influence the P-A mapping. In utilizing a variational calculus approach to define a suitable objective function, the P-A mapping can be treated as an on-line learning problem via gradient descent using partial derivatives. Our central theoretical result is to demonstrate topdown modulation of low-level perceptual confidences via the Jacobian of the higher levels of a subsumptive P-A hierarchy. Thus, the separation of the Jacobian as a multiplying factor between levels within the objective function naturally enables the integration of abstract symbolic manipulation in the form of fuzzy deductive logic into the P-A mapping learning. We experimentally demonstrate that the resulting framework achieves significantly better accuracy than using perception-action learning without top-down modulation. We also demonstrate that it permits novel forms of context-dependant multi-level P-A mapping, applying the mechanism in the context of an intelligent driver assistance system.

В статье моделируется влияние прямых зарубежных инвестиций на диверсификацию экономики страны-импортера инвестиций на основе расширенной модели международной торговли Мелитца (2003), в которой учитывается гетерогенность фирм. Результаты показывают, что при определенных условиях прямые зарубежные инвестиции (ПЗИ) посредством вертикальных внешних эффектов способствуют росту разнообразия товаров в своей отрасли и отрасли-поставщике полуфабрикатов. Эффект вытеснения в результате усилившейся конкуренции для иностранных импортеров сильнее, чем для национальных компаний. Снижение цен на полуфабрикаты как следствие прямого зарубежного инвестирования стимулирует дальнейший приток ПЗИ в страну. Ключевые слова: прямые зарубежные инвестиции, внешние эффекты, гетерогенность фирм, диверсификация экономики, внутриотраслевая торговля, отбор фирм, динамика фирм, производительность.

In this paper, an anomaly detection approach that fuses data gathered from different nodes in a distributed wireless sensor network is proposed and evaluated. The emphasis of this work is placed on the data integrity and accuracy problem caused by compromised or malfunctioning nodes. One of the key features of the proposed approach is that it provides an integrated methodology of taking into consideration and combining effectively correlated sensor data, in a distributed fashion, in order to reveal anomalies that span through a number of neighboring sensors. Furthermore, it allows the integration of results from neighboring network areas to detect correlated anomalies/attacks that involve multiple groups of nodes. The efficiency and effectiveness of the proposed approach is demonstrated for a real use case that utilizes meteorological data collected from a distributed set of sensor nodes.

In this paper, an anomaly detection approach that fuses data gathered from different nodes in a distributed wireless sensor network is proposed and evaluated. The emphasis of this work is placed on the data integrity and accuracy problem caused by compromised or malfunctioning nodes. One of the key features of the proposed approach is that it provides an integrated methodology of taking into consideration and combining effectively correlated sensor data, in a distributed fashion, in order to reveal anomalies that span through a number of neighboring sensors. Furthermore, it allows the integration of results from neighboring network areas to detect correlated anomalies/attacks that involve multiple groups of nodes. The efficiency and effectiveness of the proposed approach is demonstrated for a real use case that utilizes meteorological data collected from a distributed set of sensor nodes.

Задача повышения результативности бизнеса всегда выдвигает проблему выбора самых эффективных направлений его обеспечения. Статья посвящена вопросам обоснования критерия эффективности бизнеса, в соответствии с требованиями которого и должны определяться те направления развития бизнеса, которые обеспечивают ему наибольшую эффективность. В статье выдвинута и подтверждена гипотеза о том, что по выбранному критерию наибольшую эффективность может обеспечивать не только вариант одновременной реализации всех возможных направлений повышения эффективности, но и вариант их внедрения по частям-в виде наборов направлений. Авторами предложена модель формирования эффективного бизнеса, использующая оптимальность по Парето и реализуемая на базе двух разработанных Алгоритмов, которая проиллюстрирована на числовом примере.

The cloud computing presents a type of assignments and systems which occupy distributed resources to execute a role in a distributed way. Cloud computing make use of the online systems on the web to assist the implementation of complicated assignments; that need huge-scale computation. It was said with the intention of in our living world; we can find it challenging to balance workloads of cloud computing among assignments (jobs or tasks) and systems (machines or nodes), so the majority of the time we have to promote a condition to unbalanced assignment problems (unequal task allocations). The present article submits a new technique to solve the unequal task allocation problems. The technique is offered in an algorithmic model and put into practice on the several groups of input to investigate the presentation and usefulness of the works. An evaluation is prepared with the presented approach. It makes sure that the proposed approach provides a better outcome by comparing with some o...

This study develops a new Sensor Fault-Tolerant methodology for two-level Centralized Hierarchical Control of isolated microgrids based on a modified Kalman filter algorithm. The main objective is to increase the reliability and safety margins of isolated smart microgrids in the presence of different sensor faults on the secondary control. Consequently, Sensor Fault-Tolerant control reduces the costs because costly redundant hardware is not required. Because of its low computing effort, speed, ease of implementation, and tuning, this method can be used in more complex control configurations, multiple sensor faults, and different hierarchical control levels. The designed Sensor Fault-Tolerant Hierarchical Control System was initially proposed for a grid-forming topology of single-phase BESSs systems connected in cascade to the microgrid. The implemented fault tolerance methodology can maintain control objectives with sensor faults. Consequently, the MG's voltage at the time of the fault does not exceed 5%, and the voltage unbalance at the common coupling point or on the critical bus is compensated to a quality reference value of less than 2%. The performance of the proposed algorithm is tested using the MATLAB/Simulink simulation platform.

This paper suggests a novel three-level model-free hierarchical learning approach that solves the reference trajectory tracking problem for control systems (CSs). The new approach consists of the low level, the intermediate level and the high level, it relies on past memorized optimal input output execution patterns and adaptively merges them using a similarity measure. The low level feedback control is carried out in a novel model-free framework using a neural network (NN) controwller tuned by Virtual Reference Feedback Tuning (VRFT) in order to linearize the closed-loop CS and to match a linear reference model. The NN controller is tuned in two phases, an offline one and an online one. Nonlinear Model Predictive Control (NMPC) is first employed in the novel offline tuning phase. The online tuning phase makes next use only of the process sign in the dynamic back-propagation mechanism that updates the NN parameters. After the NN controller is trained and the feedback CS is fixed, the optimal execution patterns (input/output patterns) are defined in terms of optimal control problems, which balance control accuracy and control effort. The input/output patterns are formulated over a feedback CS and are solved in a model-free Iterative Learning Control (ILC) framework for linear time-invariant systems at the intermediate level. Once the optimal executions are learned at the intermediate level over the feedback CS, they are stored in a database (DB). Then each time a new trajectory is to be tracked as required by the high level planner, similar patterns of executions are looked-up in the DB and are merged by the weighted average sum of most similar patterns resulted from a sort algorithm using a distance metric. The proposed approach is tested on the position control of a Single Input-Single Output nonlinear aerodynamic control system and shows trajectory tracking performance improvement with respect to the case when no learnt experience is used.

A number of ETL procedures are used in the process of loading data to data warehouse systems. Some procedures can be executed concurrently in parallel mode, while for the others there are precedence constraints. Thus, the problem in scheduling procedures for execution is similar to the problem of scheduling of jobs in multiprocessor systems. The solution to this problem has been proposed in the optimum schedule of jobs minimizing the total execution time. When optimizing the schedule for ETL procedures, minimization of the total execution time is not the primary goal. Namely, the ETL procedures provide data required for reports aimed for business users and such reports need to be prepared until the user-defined deadlines. If the deadlines are not breached, the solution is satisfactory, regardless of the total execution time. Also, one cannot assume that all ETL processes are of the same importance-some have higher priorities than the others. That is the reason why prioritization and introduction of explicit bounds to completion time for individual ETL processes is attempted with genetic algorithm (GA). This paper encompasses implementation of the algorithm, experiments with different parameters and testing the quality of obtained solutions.

Most user interfaces today present system functions by use of verbal or iconic symbols on static 2D menu pages organized in a hierarchical system [1]. This is unnatural to all human beings and must be learned, thus being a barrier between the full use and understanding of computer systems. With this problem in mind we set out to build a website and collaborative application for International Children's Center (ICC) which could be used not only across languages but across ages as well. This effort was tested on a daily basis by a multinational team consisting of students from the United States and Turkey as well as children from the respective countries. This attention to usability will not only lead to an intuitive tool for the client but also teach the students in the course how to build intuitive user interfaces.

In transportation planning, design of intersections is required some concrete decisions. It is mostly related to capacity, safety and economy. In many applications, capacity is considered as the main factor for design purpose and type of intersection is determined regarding the capacity. But it is known that safety and economy are as important as the capacity. In order to handle this problem, a multi-criteria decision making approach (AHP) is used. Four intersection types are used. Fuel consumption, emission rates, delay, cost of intersection type and safety parameters are taken into account in the decision process. These intersection types are tested by SIDRA Intersection software using the parameters listed above. The data obtained by SIDRA software is used in the AHP model. Weights of the factors used in the AHP model are varied considering the views of capacity and economy. And results and applicability of the model are discussed.

ABSTRACT. Modelica is an object-oriented language for modeling of large and heterogeneous physical systems. Typical applications include mechatronic models in robotics, automotive and aerospace applications involving mechanical, electrical, ...

Există în matematică "Matematicile non-comutative " de Alain Connes (Connes. 1994). Ele se aplică în fizica cuantică în cazuri speciale, nu intru în amănunte tehnice. În fizică, inclusiv în cea subatomică/cuantică, se poate ca, plecând de la cauze, să se determine efectele ; dar şi invers, plecând de la efecte, să se pună în evidenţă cauzele. Dar ce se întâmplă în fizica subcuantică 0 2 E E

This study develops a new Sensor Fault-Tolerant methodology for two-level Centralized Hierarchical Control of isolated microgrids based on a modified Kalman filter algorithm. The main objective is to increase the reliability and safety margins of isolated smart microgrids in the presence of different sensor faults on the secondary control. Consequently, Sensor Fault-Tolerant control reduces the costs because costly redundant hardware is not required. Because of its low computing effort, speed, ease of implementation, and tuning, this method can be used in more complex control configurations, multiple sensor faults, and different hierarchical control levels. The designed Sensor Fault-Tolerant Hierarchical Control System was initially proposed for a grid-forming topology of single-phase BESSs systems connected in cascade to the microgrid. The implemented fault tolerance methodology can maintain control objectives with sensor faults. Consequently, the MG's voltage at the time of the fault does not exceed 5%, and the voltage unbalance at the common coupling point or on the critical bus is compensated to a quality reference value of less than 2%. The performance of the proposed algorithm is tested using the MATLAB/Simulink simulation platform.

В статье рассматривается одна из основных составляющих агентской проблемы: асимметрия информации и возможность получения менеджментом частных выгод в ущерб собственникам. Наличие крупного собственника-аутсайдера может привести как к усилению контроля над менеджерами, так и к его сговору с ними. В работе представлена поведенческая модель, описывающая эту ситуацию. Модель качественно подтверждает результаты эмпирических исследований о распространенности явления сговора в российской действительности.

AHP (analytic hierarchy process) is used to construct coherent aggregate results from preference data provided by decision makers. Pairwise comparison, used by AHP, shares a common weakness with other input formats used to represent user preferences, namely, that the input mode is static. In other words, users must provide all the preference data at the same time, and the criteria must be completely defined from the start. To overcome this weakness, we propose a framework that allows users to provide partial and/or incomplete preference data at multiple times. Since this is a complicated issue, we specifically focus on a particular aspect as a first attempt within this framework. For that reason, we reexamine a mechanism to achieve consistency in AHP, i.e. a linearization process, which provides consistency when adding a new element to the decision process or when withdrawing an obsolete criterion under the dynamic input mode assumption. An algorithm is developed to determine the new priority vector from the users' new input. Finally, we apply the new process to a problem of interest in the water field, specifically, the adoption of a suitable leak control policy in urban water supply.

The article presents a cognitive model of the choice that residents do moving from one region to another, depending on their individual preferences for public services and actual services provided by regional administrations. The practical benefit of this model is the possible increase in the effectiveness of public administration at the central and regional levels by understanding the processes of why and how people move between territories. Effective satisfaction of heterogeneous preferences of the population requires the state to take a federative approach to the governance over its territories. The federal principles presuppose the decentralization of power that means that regions have degree of autonomy. The latter allows local bureaucracies to independently determine the parameters of public services, and fiscal federalism gives regions independence in the formation of territorial budgets. This condition forces jurisdictions to compete for the population: local bureaucracies b...

Cost-parity games are a fundamental tool in system design for the analysis of reactive and distributed systems that recently have received a lot of attention from the formal methods research community. They allow to reason about the time delay on the requests granted by systems, with a bounded consumption of resources, in their executions. In this paper, we contribute to research on Cost-parity games by combining them with hierarchical systems, a successful method for the succinct representation of models. We show that determining the winner of a Hierarchical Cost-parity Game is PSpace-complete, thus matching the complexity of the proper special case of Hierarchical Parity Games. This shows that reasoning about temporal delay can be addressed at a free cost in terms of complexity.

An automated maneuver control framework for a remotely operate vehicle (ROV) is presented. This framework entails a three-layered control architecture, a principled approach to design and implementation within the architecture, and hybrid systems design techniques. The control architecture is structured according to the principle of composition of vehicle motions from a minimal set of elemental maneuvers that are designed and