322 research outputs found
Model Checking ofWorkflow Nets with Tables and Constraints
Many operations in workflow systems are dependent on database tables. The
classical workflow net and its extensions (e.g., worflow net with data) cannot
model these operations so that some related errors cannot be found by them.
Recently, workflow nets with tables (WFT-nets) were proposed to remedy such a
flaw. However, when the reachability graph of a WFT-net is constructed by their
method, some pseudo states are possibly generated since it does not consider
the guards that constrain the enabling and firing of transitions. Additionally,
they only considered the soundness property that just represents a single
design requirement, so that many other requirements, especially those related
to tables, cannot be analyzed. In this paper, therefore, we re-define the
WFT-net by augmenting constraints of guards to it and re-name it as workflow
net with tables and constraints (WFTC-net). We propose a new method to generate
the state reachability graphs (SRG) of WFTC-nets such that SRG can avoid pseudo
states, due to the consideration of the guards in it. To represent design
requirements related to database operations, we define database-oriented
computation tree logic (DCTL), to represent more design requirements. We design
the model checking algorithms of DCTL based on the SRG of WFTC-nets and develop
a tool. Experiments on a number of public benchmarks show the usefulness of our
methods
Verifying Computation Tree Logic of Knowledge via Knowledge-Oriented Petri Nets and Ordered Binary Decision Diagrams
Computation Tree Logic of Knowledge (CTLK) can specify many requirements of privacy and security of multi-agent systems (MAS). In our previous papers, we defined Knowledge-oriented Petri Net (KPN) to model MAS, proposed similar reachability graph to verify CTLK, gave their model checking algorithms and developed a related tool. In this paper, we use the technique of Ordered Binary Decision Diagrams (OBDD) to encode similar reachability graph in order to alleviate the state explosion problem, and verify more epistemic operators of CTLK. We design the corresponding symbolic model checking algorithms and improve our tool. We compare our model and method with MCMAS that is the state-of-the-art CTLK model checker, and experiments illustrate the advantages of our model and method. We also explain the reasons why our model and method can obtain better performances
Transaction Fraud Detection via Spatial-Temporal-Aware Graph Transformer
How to obtain informative representations of transactions and then perform
the identification of fraudulent transactions is a crucial part of ensuring
financial security. Recent studies apply Graph Neural Networks (GNNs) to the
transaction fraud detection problem. Nevertheless, they encounter challenges in
effectively learning spatial-temporal information due to structural
limitations. Moreover, few prior GNN-based detectors have recognized the
significance of incorporating global information, which encompasses similar
behavioral patterns and offers valuable insights for discriminative
representation learning. Therefore, we propose a novel heterogeneous graph
neural network called Spatial-Temporal-Aware Graph Transformer (STA-GT) for
transaction fraud detection problems. Specifically, we design a temporal
encoding strategy to capture temporal dependencies and incorporate it into the
graph neural network framework, enhancing spatial-temporal information modeling
and improving expressive ability. Furthermore, we introduce a transformer
module to learn local and global information. Pairwise node-node interactions
overcome the limitation of the GNN structure and build up the interactions with
the target node and long-distance ones. Experimental results on two financial
datasets compared to general GNN models and GNN-based fraud detectors
demonstrate that our proposed method STA-GT is effective on the transaction
fraud detection task
Checking Data-Flow Errors Based on The Guard-Driven Reachability Graph of WFD-Net
In order to guarantee the correctness of workflow systems, it is necessary to check their data-flow errors, e.g., missing data, inconsistent data, lost data and redundant data. The traditional Petri-net-based methods are usually based on the reachability graph. However, these methods have two flaws, i.e., the state space explosion and pseudo states. In order to solve these problems, we use WFD-nets to model workflow systems, and propose an algorithm for checking data-flow errors based on the guard-driven reachability graph (GRG) of WFD-net. Furthermore, a case study and some experiments are given to show the effectiveness and advantage of our method
Static Deadlock Detection for Rust Programs
Rust relies on its unique ownership mechanism to ensure thread and memory
safety. However, numerous potential security vulnerabilities persist in
practical applications. New language features in Rust pose new challenges for
vulnerability detection. This paper proposes a static deadlock detection method
tailored for Rust programs, aiming to identify various deadlock types,
including double lock, conflict lock, and deadlock associated with conditional
variables. With due consideration for Rust's ownership and lifetimes, we first
complete the pointer analysis. Then, based on the obtained points-to
information, we analyze dependencies among variables to identify potential
deadlocks. We develop a tool and conduct experiments based on the proposed
method. The experimental results demonstrate that our method outperforms
existing deadlock detection methods in precision
ASIAM-HGNN: Automatic Selection and Interpretable Aggregation of Meta-Path Instances for Heterogeneous Graph Neural Network
In heterogeneous information network (HIN)-based applications, the existing methods usually use Heterogeneous Graph Neural Networks (HGNN) to handle some complex tasks. However, these methods still have some shortcomings: 1) they manually pre-select some meta-paths and thus some important ones are missing, while the missing ones still contains the information and features of the node in the entire graph structure; and 2) they have no high interpretability since they do not consider the logical sequences in an HIN. In order to deal with them, we propose ASIAM-HGNN: a heterogeneous graph neural network combined with the automatic selection and interpretable aggregation of meta-path instances. Our model can automatically filter important meta paths for each node, while preserving the logical sequence between nodes, so as to solve the problems existing in other models. A group of experiments are conducted on real-world datasets, and the results demonstrate that the models learned by our method have a better performance in most of task scenarios
De novo characterization of Larix gmelinii (Rupr.) Rupr. transcriptome and analysis of its gene expression induced by jasmonates
BACKGROUND: Larix gmelinii is a dominant tree species in China’s boreal forests and plays an important role in the coniferous ecosystem. It is also one of the most economically important tree species in the Chinese timber industry due to excellent water resistance and anti-corrosion of its wood products. Unfortunately, in Northeast China, L. gmelinii often suffers from serious attacks by diseases and insects. The application of exogenous volatile semiochemicals may induce and enhance its resistance against insect or disease attacks; however, little is known regarding the genes and molecular mechanisms related to induced resistance. RESULTS: We performed de novo sequencing and assembly of the L. gmelinii transcriptome using a short read sequencing technology (Illumina). Chemical defenses of L. gmelinii seedlings were induced with jasmonic acid (JA) or methyl jasmonate (MeJA) for 6 hours. Transcriptomes were compared between seedlings induced by JA, MeJA and untreated controls using a tag-based digital gene expression profiling system. In a single run, 25,977,782 short reads were produced and 51,157 unigenes were obtained with a mean length of 517 nt. We sequenced 3 digital gene expression libraries and generated between 3.5 and 5.9 million raw tags, and obtained 52,040 reliable reference genes after removing redundancy. The expression of disease/insect-resistance genes (e.g., phenylalanine ammonialyase, coumarate 3-hydroxylase, lipoxygenase, allene oxide synthase and allene oxide cyclase) was up-regulated. The expression profiles of some abundant genes under different elicitor treatment were studied by using real-time qRT-PCR. The results showed that the expression levels of disease/insect-resistance genes in the seedling samples induced by JA and MeJA were higher than those in the control group. The seedlings induced with MeJA elicited the strongest increases in disease/insect-resistance genes. CONCLUSIONS: Both JA and MeJA induced seedlings of L. gmelinii showed significantly increased expression of disease/insect-resistance genes. MeJA seemed to have a stronger induction effect than JA on expression of disease/insect-resistance related genes. This study provides sequence resources for L. gmelinii research and will help us to better understand the functions of disease/insect-resistance genes and the molecular mechanisms of secondary metabolisms in L. gmelinii
Environmental stress level evaluation approach based on physical model and interval grey association degree
AbstractAssociating environmental stresses (ESs) with built-in test (BIT) output is an important means to help diagnose intermittent faults (IFs). Aiming at low efficiency in association of traditional time stress measurement device (TSMD), an association model is built. Thereafter, a novel approach is given to evaluate the integrated environmental stress (IES) level. Firstly, the selection principle and approach of main environmental stresses (MESs) and key characteristic parameters (KCPs) are presented based on fault mode, mechanism, and ESs analysis (FMMEA). Secondly, reference stress events (RSEs) are constructed by dividing IES into three stress levels according to its impact on faults; and then the association model between integrated environmental stress event (IESE) and BIT output is built. Thirdly, an interval grey association approach to evaluate IES level is proposed due to the interval number of IES value. Consequently, the association output can be obtained as well. Finally, a case study is presented to demonstrate the proposed approach. Results show the proposed model and approach are effective and feasible. This approach can be used to guide ESs measure, record, and association. It is well suited for on-line assistant diagnosis of faults, especially IFs
Guard-Function-Constraint-Based Refinement Method to Generate Dynamic Behaviors of Workflow Net with Table
In order to model complex workflow systems with databases, and detect their data-flow errors such as data inconsistency, we defined Workflow Net with Table model (WFT-net) in our previous work. We used a Petri net to describe control flows and data flows of a workflow system, and labeled some abstract table operation statements on transitions so as to simulate database operations. Meanwhile, we proposed a data refinement method to construct the state reachability graph of WFT-nets, and used it to verify some properties. However, this data refinement method has a defect, i.e., it does not consider the constraint relation between guard functions, and its state reachability graph possibly has some pseudo states. In order to overcome these problems, we propose a new data refinement method that considers some constraint relations, which can guarantee the correctness of our state reachability graph. What is more, we develop the related algorithms and tool. We also illustrate the usefulness and effectiveness of our method through some examples
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