Transition Graph Research Articles

A stochastic dynamic programming for maintenance planning of an emergency helicopter

Emergency/rescue helicopters are an essential part of the healthcare systems. Every helicopter should be kept in its best possible operational mode to save the life of the people in danger. For achieving this goal, using an optimal maintenance planning is crucial, which involves a periodic decision about repair or replacement of the components in the helicopter. But, in the considered case study, the spare part inventory is limited and cannot be easily replenished. Also, an observation in this case study is that a repaired component may have a shorter probabilistic lifetime (i.e. time to next failure) in contrast to a brand-new one. The best sequence of decisions can be made for each day of a given planning horizon, when different probabilistic trade-offs for every mission hour are taken into account. The problem is formulated in the framework of a stochastic dynamic program (SDP). For obtaining a fast near-optimal policy, an approximate dynamic program (ADP) is developed, which is based on the Monte-Carlo sampling of the possible paths in the corresponding transition graph of the SDP. A numerical experiment shows its gradual convergence toward an optimal policy as it spends more time in the search space of the SDP.

Detecting Performance Variance for Parallel Applications Without Source Code

For parallel applications, performance variance is a critical issue that can degrade performance and make applications’ behavior difficult to explain. Therefore, users and application developers should be able to detect and diagnose performance variance. Previous detection methods either introduce too much overhead and slow down applications, or rely on nontrivial source code analysis, which is impractical for production-run parallel systems. In this article, we propose <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Vapro</small> , a framework for detecting and diagnosing performance variance in production-run parallel systems. Our method is based on an observation that most parallel programs contain code snippets that are executed repeatedly with a fixed workload and can be utilized to detect performance variance. We present State Transition Graph (STG) to track program execution and then do light-weight workload analysis on STG to locate performance variance. <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Vapro</small> is able to successfully identify these snippets at runtime even without program source code. To diagnose the discovered variation, <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Vapro</small> uses a progressive diagnosis method based on a hybrid model combining variance breakdown and statistical analysis. According to evaluating results, <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Vapro</small> 's performance overhead is only 1.38% on average. <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Vapro</small> can identify performance variance in real applications caused by hardware issues, such as memory and IO. The standard deviation of the execution time is decreased by up to 73.5% when the identified variance is fixed. <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Vapro</small> achieves 30.0% larger detection coverage than the state-of-the-art variance detection approach based on source code analysis.

Mapping out the glassy landscape of a mesoscopic elastoplastic model.

We develop a mesoscopic model to study the plastic behavior of an amorphous material under cyclic loading. The model is depinning-like and driven by a disordered thresholds dynamics that is coupled by long-range elastic interactions. We propose a simple protocol of "glass preparation" that allows us to mimic thermalization at high temperatures as well as aging at vanishing temperature. Various levels of glass stabilities (from brittle to ductile) can be achieved by tuning the aging duration. The aged glasses are then immersed into a quenched disorder landscape and serve as initial configurations for various protocols of mechanical loading by shearing. The dependence of the plastic behavior upon monotonous loading is recovered. The behavior under cyclic loading is studied for different ages and system sizes. The size and age dependence of the irreversibility transition is discussed. A thorough characterization of the disorder-landscape is achieved through the analysis of the transition graphs, which describe the plastic deformation pathways under athermal quasi-static shear. In particular, the analysis of the stability ranges of the strongly connected components of the transition graphs reveals the emergence of a phase-separation like process associated with the aging of the glass. Increasing the age and, hence, the stability of the initial glass results in a gradual break-up of the landscape of dynamically accessible stable states into three distinct regions: one region centered around the initially prepared glass phase and two additional regions characterized by well-separated ranges of positive and negative plastic strains, each of which is accessible only from the initial glass phase by passing through the stress peak in the forward and backward, respectively, shearing directions.

Determining the components of the structural-automatic model of firing a single target in armor protection with fragmentation-beam projectiles of directed action in a series of three shots based on the reference graph of states

The problem of determining the components of the structural-automatic model is solved by creating a graph of states and transitions. The purpose of the process is to form a formalized expression of the object of study in the form of a structural-machine model of the process of firing a mobile armored vehicle with a series of three shots with fragmentation-beam projectiles of directional action. This model can be further practically implemented during the development of the latest samples of fire resistance in order to reduce errors at the stage of system design. This approach reduces the cost of design and production of prototypes by up to 25 %. This paper considers the process involving interrelated elements of the components of a system while accounting for all possible variants of its behavior from the moment of detection to the failure of a single target in armor protection to perform tasks as intended. The execution of a fire task is considered as a set of certain procedures characterized by the average value of their duration. The explosive destruction of the hull of each fragmentation-beam projectile is characterized by the self-propagation of the reaction of explosive transformations based on tabular data on an armored combat vehicle. Appropriate procedures (phases) of firing a single target in armor protection are advisable to formalize to create preconditions for obtaining the value of a statistical indicator of the effectiveness of causing damage to the target and to study further alternative options for this process. For the proposed structural-automatic model of the process of firing a single target in armor protection with a series of fragmentation-beam projectiles of directional action, validation and verification were carried out, which demonstrated the convergence of the results that exceeded 60 %. The use of the structural-automatic model's components proposed in this work increases the probability of performing a fire task for the first shot from 0.23 to 0.88, for the second – from 0.35 to 0.95, for the third – from 0.45 to 0.98

The configuration space of a robotic arm over a graph

In this paper, we investigate the configuration space [Formula: see text] associated with the movement of a robotic arm of length [Formula: see text] on a grid over an underlying graph [Formula: see text], anchored at a vertex [Formula: see text]. We study an associated poset with inconsistent pairs (PIP) [Formula: see text] consisting of indexed paths on [Formula: see text]. This PIP acts as a combinatorial model for the robotic arm, and we use [Formula: see text] to show that the space [Formula: see text] is a CAT(0) cubical complex, generalizing work of Ardila, Bastidas, Ceballos, and Guo. This establishes that geodesics exist within the configuration space, and yields explicit algorithms for moving the robotic arm between different configurations in an optimal fashion. We also give a tight bound on the diameter of the robotic arm transition graph — the maximal number of moves necessary to change from one configuration to another — and compute this diameter for a large family of underlying graphs [Formula: see text].

Cyber-attack research for integrated energy systems by the correlated matrix based object-oriented modeling method

The rise of an integrated energy system requires the integration of multiple sources of energy to be embraced and transited over the power grid; that means the information and communication systems of traditional power systems will be extended, and their complexity will be increased. As the information and communication systems play a more important role in the infrastructure of the power system, a cyber-attack on them may have an impact on the power system and cause a serious threat to the integrated energy system. To analyze the threat to the complex and integrated system, some researchers provide some modeling methods to study the impact of cyber-attacks on the information and communication systems, such as the Attack Tree Model, Attack Graph Model, Petri Net Model for cyber-attack, Attack Description Language Model, State Transition Graph Model, etc. However, these modeling methods have some shortcomings. For example, they cannot describe the systematical cyber-attack and show the secure status during the cyber-attack; it is hard for them to analyze the larger and more complicated information and communication systems. To overcome the shortages, in this paper, a correlated matrix-based object-oriented model is proposed for cyber-attack modeling. With this model, the relationship between the attacker and victim can be directly built; the cyber-attack path and packets from the attacker can be tracked; and the status of the nodes and links can be shown during a cyber-attack. There are two steps to build the cyber-attack model. Firstly, the procedure and approach of the cyber-attack will be modeled by an object-oriented method; then, a correlated matrix model will be built for network topology, attack path, and attack procedure. By combining these two models, the whole cyber-attack model is created. Finally, to demonstrate the modeling method and its benefits, we use the MITM (Man-in-the-middle Attack) attack on measurement data of an AVC (Automation Voltage Control) system as examples, and build a hardware-in-the-loop (HIL) co-simulation platform to verify the model.

Quantum annealing with special drivers for circuit fault diagnostics

We present a very general construction for quantum annealing protocols to solve Combinational Circuit Fault Diagnosis problems that restricts the evolution to the space of valid diagnoses. This is accomplished by using special local drivers that induce a transition graph on the space of feasible configurations that is regular and instance independent for each given circuit topology. Analysis of small instances shows that the energy gap has a generic form, and that the minimum gap occurs in the last third of the evolution. We used these features to construct an improved annealing schedule and benchmarked its performance through closed system simulations. We found that degeneracy can help the performance of quantum annealing, especially for instances with a higher number of faults in their minimum fault diagnosis. This contrasts with the performance of classical approaches based on brute force search that are used in industry for large scale circuits.

In Search of Lost Utility: Private Location Data

The unavailability of training data is a permanent source of much frustration in research, especially when it is due to privacy concerns. This is particularly true for location data since previous techniques all suffer from the inherent sparseness and high dimensionality of location trajectories which render most techniques impractical, resulting in unrealistic traces and non-scalable methods. Moreover, time information of location visits is usually dropped, or its resolution is drastically reduced. In this paper we present a novel technique for privately releasing a composite generative model and whole high-dimensional location datasets with detailed time information. To generate high-fidelity synthetic data, we leverage several peculiarities of vehicular mobility such as its language-like characteristics (“you should know a location by the company it keeps”) or how humans plan their trips from one point to the other. We model the generator distribution of the dataset by first constructing a variational autoencoder to generate the source and destination locations, and the corresponding timing of trajectories. Next, we compute transition probabilities between locations with a feed forward network, and build a transition graph from the output of this model, which approximates the distribution of all paths between the source and destination (at a given time). Finally, a path is sampled from this distribution with a Markov Chain Monte Carlo method. The generated synthetic dataset is highly realistic, scalable, provides good utility and, nonetheless, provably private. We evaluate our model against two state-of-theart methods and three real-life datasets demonstrating the benefits of our approach.

Joint realizability of monotone Boolean functions

The study of monotone Boolean functions (MBFs) has a long history. We explore a connection between MBFs and ordinary differential equation (ODE) models of gene regulation, and, in particular, a problem of the realization of an MBF as a function describing the state transition graph of an ODE. We formulate a problem of joint realizability of finite collections of MBFs by establishing a connection between the parameterized dynamics of a class of ODEs and a collection of MBFs. We pose a question of what collections of MBFs can be realized by ODEs that belong to nested classes defined by increased algebraic complexity of their right-hand sides. As we progressively restrict the algebraic form of the ODE, we show by a combination of theory and explicit examples that the class of jointly realizable functions strictly decreases. Our results impact the study of regulatory network dynamics, as well as the classical area of MBFs. We conclude with a series of potential extensions and conjectures.

Logit Averaging: Capturing Global Relation for Session-Based Recommendation

Session-based recommendation predicts an anonymous user’s next action, whether she or he is likely to purchase based on the user’s behavior in the current session as sequences. Most recent research on session-based recommendations makes predictions based on a single-session without incorporating global relationships between sessions. It does not guarantee a better performance because item embeddings learned by solely utilizing a single session (inter-session) have less item transition information than utilizing both intra- and inter-session ones. Some existing methods tried to enhance recommendation performance by adopting memory modules and global transition graphs; however, those need more computation cost and time. We propose a novel algorithm called Logit Averaging (LA), utilizing both (i) local-level logits, which come from intra-sessions item transitions and (ii) global-level logits, which come from gathered logits of related sessions. The proposed method shows an improvement in recommendation performance in respect of accuracy and diversity through extensive experiments.

EXTENDED SOFTWARE AGING AND REJUVENATION MODEL FOR ANDROID OPERATING SYSTEM CONSIDERING DIFFERENT AGING LEVELS AND REJUVENATION PROCEDURE TYPES

A complex model based on Continuous-Time Markov Chains is proposed, which combines an extended aging and rejuvenation model taking into account different aging levels and a model of mobile device usage activity. A graph of states and transitions is constructed, which describes the proposed model without taking into account mobile device usage activity, and taking it into account. A system of Kolmogorov – Chapman differential equations is written on the basis of the states graph. A set of test simulations for conducting experimental calculations of the model and analysis of results is described. A system of differential equations for each simulation is calculated using the 4th order Runge-Kutta method. The analysis of simulations with recovery after aging-related failure and without recovery allowed to formulate the main objectives of the rejuvenation procedure in the proposed model to improve the user experience. Analysis of different rejuvenation planning strategies indicates that the most effective approach is to perform rejuvenation in the “Aging” state, when the device is already aging, but it is not yet a state with a high probability of aging-related failure. Analysis of simulations with warm and cold rejuvenation shows that this factor affects the results of the model calculation, and the application of one or another approach depends on the aging conditions and the mobile device usage activity. The developed model based on the Markov chain can be used to predict the optimal time of the rejuvenation procedure. In addition, the model considers both cold and warm rejuvenation. Further studies which take into account the real data and aging conditions are needed for proposed aging and rejuvenation model.

Vulnerability analysis of power system by modified H-index method on cascading failure state transition graph

The mechanism of the cascades and the vulnerability of the power grids have been widely concerned due to the blackouts around the word in recent years. It is urgent to propose an effective method to estimate the vulnerability of the power grids. In this paper, a modified H-index method is proposed to identify the critical lines in power grids based on the cascading failure state transition graph. First, a two-level cascading failure state transition graph is constructed according to the power flow transfer on transmission lines after the cascading failures to describe the state transfer relationship when the transmission line is cut off. Then, the state transition graph is decomposed into the fault propagation graph and the fault infection graph, respectively in view of the infectiousness and propagation of the line faults. And a vulnerable line identification method is proposed based on the modified H-index method. Finally, the simulations on the IEEE-39 bus system and the NE power grid show that the transmission lines which are prone to propagate faults or have weak anti-interferences can be identified effectively by the proposed method.

Epigenetic forest and flower morphogenesis

This paper studies the epigenetic process that leads to Angiosperms’ flower architecture (flowering plants). As a case study, we analyze the flower Arabidopsis thaliana’s GRN obtained during cell fate determination in the early stages of the flower’s development, which was constructed in a previous work using experimental data. We start by constructing and analyzing the Epigenetic Forest, a discrete representation of Waddington’s Epigenetic Landscape, obtained as the transition graph of the discrete dynamical system associated with the GRN. Next, we propose an optimization problem to model morphogenesis by defining a biologically meaningful function that accounts for the work involved in cell specialization. Finally, the problem is solved using a genetic algorithm. The optimal solution found by the algorithm correctly recovers the flower’s architecture, as observed in wild type flowers and recovered in other theoretical works. Even though the case study addresses this specific problem, the method is directly applicable to other GRN’s with attractors consisting of equilibrium points only and could be extended to the situation where there are periodic attractors.

Structure and behavior in Boolean monotonic model pools

One of the main theoretical questions in the field of discrete regulatory networks is the question what aspects of the dynamics – the structure of the state transition graph – are already imposed by structural descriptions of the network such as the interaction graph. For Boolean networks, prior work has concentrated on different versions of the Thomas conjectures that link feedback cycles in the network structure to attractor properties. Other approaches check algorithmically whether certain properties hold true for all models sharing specific structural constraints, e.g. by using model checking techniques. In this work we investigate the behavior of the pool of Boolean networks in agreement with a given interaction graph using a different approach. Grouping together states that are updated consistently across the pool we derive an equivalence relation and analyze a corresponding quotient graph on the state space. By construction this graph yields information about the dynamics of all functions in the pool. Our main result is that this graph can be computed efficiently without enumerating and analyzing all individual functions. This opens up new possibilities for applications, where such model pools arise when modeling under uncertainty.

Asynchronous Wrapper-Based Low-Power GALS Structural QDMA

The design of System-on-Chip systems using synchronous circuits involves complex clock distribution strategies, which envisage challenges for designers to integrate large-scale systems. Globally Asynchronous Locally Synchronous architectures containing asynchronous port controllers encapsulated in the self-timed wrapper have been adopted in this work. These port controllers communicate through Asynchronous Finite State Machines defined by Signal Transition Graphs are implemented adopting the C element. This GALS architecture implemented for the point-to-point interface can also be modified for the multipoint interface. The proposed methodology uses a two-phase handshake protocol to communicate between two Locally Synchronous modules as it has fewer signal transitions, which, in turn, reduces latency. In this paper, the Queue Direct Memory Access subsystem is implemented using the Vivado simulator on UltraScale+™ device at a maximum frequency of 257.4MHz, and various parameters are reported. A comparison shows that the proposed wrapper has improved latency time of 53%, with a reduction in power dissipated by 27% and an increase in gate count by 13%.

ANDROID SOFTWARE AGING AND REJUVENATION MODEL CONSIDERING THE BATTERY CHARGE

Context. A feature of mobile systems is their dependence on battery charge, which is an important factor when planning various processes, in particular when planning time of performing software rejuvenation procedure.&#x0D; Objective. The goal of this article is to develop a model of software aging process with performing rejuvenation procedure for the Android operating system considering the factor of battery charge.&#x0D; Method. A complex model based on Continuous-Time Markov Chains is proposed, which combines the software aging and rejuvenation model, the user behavior model and consider battery charge factor. A graph of states and transitions describing a complex model is constructed. Based on the formed graph the system of differential equations is written. The system was calculated using the 4th order Runge-Kutta method. The optimal time for the rejuvenation procedure can be determined when rejuvenation will not interfere with the user and will be performed before the battery is fully discharged, ie when the probability of the system being in these states is the lowest.&#x0D; Results. The simulation of the developed model for test values of transition rates is performed. Considering the battery charge model allows to avoid planning the rejuvenation procedure at a time when the mobile device is likely to have a low charge or be completely discharged.&#x0D; Conclusions. The proposed model based on the Markov chain allows to predict the start time of software rejuvenation procedure, considering both user behavior and battery level, which can have a significant impact on the predicted time. Also, the early implementation of the rejuvenation procedure may have the effect of reducing the system workload and delaying the discharge of the device, which should be checked in further studies. The expediency and importance of the consideration of battery charge factor and the need for further study of the proposed software aging and rejuvenation model are substantiated.

Graph-Feature-Enhanced Selective Assignment Network for Hyperspectral and Multispectral Data Classification

Due to rich spectral and spatial information, the combination of hyperspectral and multispectral images (MSIs) has been widely used for Earth observation, such as wetland classification. However, mining of meaningful features and effective fusion of multisource remote sensing data are still urgent problems to be solved. In this article, graph-feature-enhanced selective assignment network (GSANet) is proposed. On the one hand, a graph feature extraction module (GFEM) is designed to extract topological structure information and combine with the rich spectral–spatial information. In particular, the features obtained by convolution are first mapped to the graph feature space, and the graph convolution operation is used to achieve propagation between nodes for preserving topological structure information. Moreover, to reduce the difference of graph features resulting from the mapping function and better explore the complementary properties of multisource data, a novel graph fusion strategy-graph dependence fusion is designed. A transition graph is generated to enhance the association and interaction between different graph features, so as to avoid the information loss caused by simple fusion operation. On the other hand, a selective feature assignment module (SFAM) is developed to adaptively assign weights to different discriminative features. SFAM assigns weights to different features to selectively emphasize informative features and suppress less useful ones. Extensive experiments are conducted on two multisource remote sensing datasets, and the improvement of at least 1.27% and 0.98% compared to other state-of-the-art work demonstrates the superiority of the proposed GSANet.

СИНТЕЗ УСТРОЙСТВ УПРАВЛЕНИЯ НАПОЛЬНЫМ ТЕХНОЛОГИЧЕСКИМ ОБОРУДОВАНИЕМ ЖЕЛЕЗНОДОРОЖНОЙ АВТОМАТИКИ С ОБНАРУЖЕНИЕМ НЕИСПРАВНОСТЕЙ НА ПРОГРАММИРУЕМЫХ ЛОГИЧЕСКИХ ИНТЕГРАЛЬНЫХ СХЕМАХ

The paper describes features of synthesis of control devices for wayside technological equipment of signalling, interlocking and block systems on field-programmable gate array (FPGA). In the work the authors consider the simplest example of implementation of a shunting light signal control circuit that demonstrates the synthesis technique. The most important stage is the definition of all interacting objects, input and output data, states and conditions of transition between states. Based on this initial information, a transition graph is formed. Next, a functional basis for implementation is selected (in this case, these are FPGA), and then a coding method to protect the automaton in operation is determined. In order to implement reliable and secure devices, well-known methods are used to ensure these properties for technical objects. The technique allows not only synthesizing control devices for automation objects, but also implementing software tools for their operation and test diagnostics.

Algorithm Design for Deterministic Finite Automata for a Given Regular Language with Prefix Strings

Computer Science and Engineering have given us the field of automata theory, one of the largest areas that is concerned with the efficiency of an algorithm in solving a problem on a computational model. Various classes of formal languages are represented using Chomsky hierarchy. These languages are described as a set of specific strings over a given alphabet and can be described using state or transition diagrams. The state/transition diagram for regular languages is called a finite automaton which is used in compiler design for recognition of tokens. Other applications of finite automata include pattern matching, speech and text processing, CPU machine operations, etc. The construction of finite automata is a complicated and challenging process as there is no fixed mathematical approach that exists for designing Deterministic Finite Automata (DFA) and handling the validations for acceptance or rejection of strings. Consequently, it is difficult to represent the DFA’s transition table and graph. Novel learners in the field of theoretical computer science often feel difficulty in designing of DFA The present paper proposes an algorithm for designing of deterministic finite automata (DFA) for a regular language with a given prefix. The proposed method further aims to simplify the lexical analysis process of compiler design.

GenSelfHolding: Fusing Selfish Mining and Block Withholding Attacks on Bitcoin Revisited

Due to the monetary value of Bitcoin, the most influential digital cryptocurrency in the world, Bitcoin has naturally become a valuable target of attacks, resulting in the emergence of many attack strategies on it. Among those attack strategies, selfish mining and block withholding attacks are two typical ones and attackers can obtain higher revenues under certain conditions than with an honest mining strategy. However, the combination of them will be a new type and more serious attack, which has not been analyzed in depth. In this paper, we propose GenSelfHolding, a general combined attack model with one selfish mining pool and random multiple honest pools on Bitcoin. Based on Markov chain, a general state transition graph and a general state distribution probability are presented to describe the internal features of our model. A general principle is then provided to calculate the attacker’s revenue. In addition, we give a detailed proof of the unique stable distribution of state transition probabilities. Such proof is an essential prerequisite for us to further present stable attacker revenue expressions under two specific scenarios, the GenSelfHolding model with two/three honest mining pools. Simulation results validate that the revenues of the attacker in these two specific models can reach up to 40% higher than those of classic selfish attackers in some cases.