Abstract Annual audit planning is a multi-criteria decision-making problem faced by internal departments of all organizations. Due to the constrained resources, process primarily involves analysis and evaluation complex factors for selecting auditable units that maximize full potential audit. Previous research on only focused goal risk minimization applied ranking methods prioritize alternatives. In order enable activities add more value organization, integrated risk-based proposed assist...

Presents a method for finding patterns in 3D graphs. Each node graph is an undecomposable or atomic unit and has label. Edges are links between the units. Patterns rigid substructures that may occur after allowing arbitrary number of whole-structure rotations translations as well small (specified by user) edit operations graph. (When pattern appears only been modified, we call appearance "approximate occurrence.") The include relabeling node, deleting inserting node. proposed based on...

Abstract Brittle material usually contains plenty of cracks or micro‐cracks, which raises a question that how pre‐existing crack affects running as they are approaching. In order to investigate such issue, impact experiments were conducted by using double semi‐circle (DCSC) specimens. Polymethyl methacrylate (PMMA) was selected make the DCSC specimens, and modified SHPB system used perform tests. The finite difference code AUTODYN employed simulate propagation behavior path, simulated paths...

The visual information provided by applications facilitating urban communications such as Google Street View and Waze scene report is intuitionistic useful since it conforms to human cognitive habits. However, current street view services cannot provide real-time information, the service passive. An on-demand visual-information-providing mechanism still unavailable. In this paper, we develop crowdsourcing-based Real-time Share (RVShare) system, which provides pictures of requested locations...

End-to-end models are favored in automatic speech recognition (ASR) because of their simplified system structure and superior performance.Among these models, Transformer Conformer have achieved state-of-the-art accuracy which self-attention plays a vital role capturing important global information.However, the time memory complexity increases squarely with length sentence.In this paper, prob-sparse mechanism is introduced into to sparse computing process order accelerate inference speed...

As an essential element of higher education, course planning at the program level is a complicated multi-criteria decision making (MCDM) problem. In addition, process tailored to sustainable development exceptionally important sustaining quality academic programs. However, there scarcity research on problem operational due diverse set stakeholder requirements in practice. Motivated by challenge, this study proposes innovative MCDM model for based He-Xie management theory. introduced...

We focus on the dynamic Routing and Spectrum Allocation (RSA) problem in EONs with mixed line rates. To solve RSA efficiently, we decompose into routing spectrum allocation sub-problems. For sub-problem, propose an efficient multi-constrained algorithm, Sorted Feasible Paths Searching (SFPS), to find shortest feasible paths for traffic demands. a strategy named Adaptive Segmentation (AS) allocate non-commensurate demands of Simulation results prove that proposed algorithm is time-efficient...

Curriculum planning is an important but complex and challenging decision-making problem at universities. There a growing interest in curriculum problem. However, the body of research on process using analytical methods still small. Additionally, prior focused individual or making study plan for students. program level under-researched topic. A robust model has not been constructed to address selection credit allocation problems simultaneously. To help educational leaders make most...

The signed digraph (SDG) method for fault diagnosis, which is one of the model-based methods, has been widely applied in chemical industry recent years. However, how to elicit appropriate thresholds SDG a very difficult problem. This study presents new hybrid combining with dynamic kernel partial least-squares (DKPLS) and support vector regression (SVR) diagnosis. Using relationships each variable SDG, series DKPLS-SVR models are built estimate values measured variables process. difference...

This paper presents some practical applications of signed directed graphs (SDGs) to computeraided hazard and operability study (HAZOP) fault diagnosis, based on an analysis the SDG theory. The is modeled for inversion synthetic ammonia, which highly dangerous in process industry, HAZOP diagnosis model are presented. A new reasoning method, whereby inverse inference combined with forward inference, presented implement a breadth-first algorithm consistency rules. Compared conventional engines,...

In recent years, there has been an exponential growth in the traffic of cloud data centers networks (DCNs). More and more users are outsourcing their computing demands services to DCNs. To handle such increases workload a scalable manner, many technologies have proposed provide dynamic topology network so as adapt traffic. One representative scheme is optical switching architecture (OSA) it provides tremendous flexibility. However, OSA requires too much time (10 ms) reconfigure topology....

An integrated implementation solution and theoretical framework of fault diagnosis approach based on probabilistic signed digraph (PSDG) is proposed applied to a gas fractionation unit. On the basis primary method PSDG presented in our previous work, complete constructed, including its definition reasoning implementation. Nodes branches contain uncertain information their priori conditional parameters are decided by using little knowledge studied plant; thus, model can be built properly....

Class incremental learning needs to deal with a dynamic environment where data class appears incrementally, it is challenge learn new knowledge while preserving what has already been learned. On the other hand, due limited storage of online scenario, algorithm usually obstructed frequently scan or simply store all historical data, another reduce for algorithm. Few existing work have addressed above challenges simultaneously. In this paper, we propose Fisher Discriminant Analysis Random...