Multi-Perspective Data Fusion Framework Based on Hierarchical BERT: Provide Visual Predictions of Business Processes

Predictive Business Process Monitoring(PBPM)is a significant research area in Business Process Management(BPM)aimed at accurately forecasting future behavioral events.At present,deep learning methods are widely cited in PBPM research,but no method has been effective in fusing data information into the control flow for multi-perspective process prediction.Therefore,this paper proposes a process prediction method based on the hierarchical BERT and multi-perspective data fusion.Firstly,the first layer BERT network learns the correlations between different category attribute data.Then,the attribute data is integrated into a weighted event-level feature vector and input into the second layer BERT network to learn the impact and priority relationship of each event on future predicted events.Next,the multi-head attention mechanism within the framework is visualized for analysis,helping to understand the decision-making logic of the framework and providing visual predictions.Finally,experimental results show that the predictive accuracy of the framework surpasses the current state-of-the-art research methods and significantly enhances the predictive performance of BPM.

PERFORMANCE EVALUATION METHOD FOR BUSINESS PROCESS OF MACHINERY MANUFACTURER BASED ON DEA/AHP HYBRID MODEL

A set of indices for performance evaluation for business processes with multiple inputs and multiple outputs is proposed, which are found in machinery manufacturers. Based on the traditional methods of data envelopment analysis （DEA） and analytical hierarchical process （AHP）, a hybrid model called DEA/AHP model is proposed to deal with the evaluation of business process performance. With the proposed method, the DEA is firstly used to develop a pairwise comparison matrix, and then the AHP is applied to evaluate the performance of business process using the pairwise comparison matrix. The significant advantage of this hybrid model is the use of objective data instead of subjective human judgment for performance evaluation. In the case study, a project of business process reengineering （BPR） with a hydraulic machinery manufacturer is used to demonstrate the effectiveness of the DEA/AHP model.

Formalization and Verification of Business Process Modeling Based on UML and Petri Nets

In order to provide a quantitative analysis and verification method for activity diagrams based business process modeling, a formal definition of activity diagrams is introduced. And the basic requirements for activity diagrams based business process models are proposed. Furthermore, the standardized transformation technique between business process models and basic Petri nets is presented and the analysis method for the soundness and well-structured properties of business processes is introduced.

Competency Driven Resource Evaluation Method for Business Process Intelligence

Enterprises are continuously aiming at improving the execution of processes to achieve a competitive edge.One of the established ways of improving process performance is to assign the most appropriate resources to each task of the process.However,evaluations of business process improvement approaches have established that a method that can guide decision-makers to identify the most appropriate resources for a task of process improvement in a structured way,is missing.It is because the relationship between resources and tasks is less understood and advancement in business process intelligence is also ignored.To address this problem an integrated resource classification framework is presenting that identifies competence,suitability,and preference as the relationship of task with resources.But,only the competence relationship of human resources with a task is presented in this research as a resource competence model.Furthermore,the competency calculation method is presented as a user guider layer for business process intelligencebased resource competence evaluation.The computed capabilities serve as a basic input for choosing the most appropriate resources for each task of the process.Applicability of method is illustrated through a heathcare case study.

PERFORMANCE-DRIVEN BUSINESS PROCESS MANAGEMENT METHODOLOGY FOR SMALL AND MEDIUM SIZED-ENTERPRISES

Based on the analysis of the common limitations of business processmanagement (BPM) methodologies and the requirements of small and medium sized-enterprises (SMEs),the importance of a 'performance construct' of BPM methodologies is identified, a six-phaseperformance-driven BPM methodology for the production and operation processes of Chinese SMEs isdeveloped. A case study on the process management of a medium-sized enterprise shows a successfulexample of running the methodology.

On Computing the Suitability of Non-Human Resources for Business Process Analysis

Business process improvement is a systematic approach used by several organizations to continuously improve their quality of service.Integral to that is analyzing the current performance of each task of the process and assigning the most appropriate resources to each task.In continuation of our previous work,we categorize resources into human and non-human resources.For instance,in the healthcare domain,human resources include doctors,nurses,and other associated staff responsible for the execution of healthcare activities;whereas the non-human resources include surgical and other equipment needed for execution.In this study,we contend that the two types of resources(human and non-human)have a different impact on the process performance,so their suitability should be measured differently.However,no work has been done to evaluate the suitability of non-human resources for the tasks of a process.Consequently,it becomes difficult to identify and subsequently overcome the inefficiencies caused by the non-human resources to the task.To address this problem,we present a three-step method to compute a suitability score of non-human resources for the task.As an evaluation of the proposed method,a healthcare case study is used to illustrate the applicability of the proposed method.Furthermore,we performed a controlled experiment to evaluate the usability of the proposed method.The encouraging response shows the usefulness of the proposed method.

Remaining Time Prediction for Business Processes with Concurrency Based on Log Representation

Remaining time prediction of business processes plays an important role in resource scheduling and plan making.The structural features of single process instance and the concurrent running of multiple process instances are the main factors that affect the accuracy of the remaining time prediction.Existing prediction methods does not take full advantage of these two aspects into consideration.To address this issue,a new prediction method based on trace representation is proposed.More specifically,we first associate the prefix set generated by the event log to different states of the transition system,and encode the structural features of the prefixes in the state.Then,an annotation containing the feature representation for the prefix and the corresponding remaining time are added to each state to obtain an extended transition system.Next,states in the extended transition system are partitioned by the different lengths of the states,which considers concurrency among multiple process instances.Finally,the long short-term memory(LSTM)deep recurrent neural networks are applied to each partition for predicting the remaining time of new running instances.By extensive experimental evaluation using synthetic event logs and reallife event logs,we show that the proposed method outperforms existing baseline methods.

Mobile businessprocess modelingusinghigh level Petri nets

This paper aims at providing an effective modeling methods for more and more mobile business applications. First a high level Petri nets method-Xml nets is introduced, which combines the advantage of Petri nets and XML. Petri nets have strict mathematics and intuitionistic diagram ex- pression way, rich system describing means and system behavior analytical technology, and the re- lated powerful supporting tools. XML, as an extensible markup language, is already a information description de facto standard. XML nets could be utilized to model both the controlling flow and the data flow of mobile business process effectively, which consequently enables the analysis and optimi- zation of the mobile business processes and could be utilized to simulate the execution of the mobile business process with the Petri nets tools to improve the system execution efficiency. In this paper, to demonstrate the modeling of the controlling flow and data flow of mobile business process, an in- strument repair business case is modeled with XML nets.

A Template-Based Approach for Automatic Mapping between Business Process and BPEL Process

In order to support just-in-time reconfiguration of business process execution language （BPEL） process, a template-based mapping method is proposed to map business level process to BPEL process. The method builds up mapping relationships between the key points of business level process and BPEL process, which helps users to adjust the business level process with simplified operations, and automatically maps the changes to BPEL. In addition, a case of the application of the method in a clothing enterprise was illustrated.

Analyzing and Designing Business Processes Management System Based on Transformation of Instantiated Ontology’s State

The paper discusses efforts of finding a simple and transparent method to analyze business processes and developing its management system architecture. By introducing ontology and its state, the approach tried to find a unified representation and a flexible choreography of business processes. The main idea of the paper is the transformation of ontology＇s states, which are the most important scenarios of enterprises. The business activity composition, that is, case composition based on an AI technique, Case Based Reason （CBR）, which is to solve new problems by retrieving solutions to previous problems, and then store the modified solution. The main interest in CBR relies on that it allows a system to avoid past failures and exploit past successes.

Research on Business Processes Optimization for Agile Manufacturing

Based on macroscopic and synthetic approaches, especially information entropy approach, the quantification of the flexible degree and order degree of business processes is studied. According to the outcome of above analysis, a conceptual model of optimizing business processes is proposed which supports to construct dynamic stable business processes. The research above has been applied in project 863/SDDAC-CIMS, and achieved primary benefits.

Diagnosing and optimizing enterprise business process using process walkthrough method

The basic requirements of "business process walkthrough" method were clarified and the diagnostic way of process problem of enterprise was discussed. The business process problems can be summarized as process structure defects, lack of supporting mechanisms and lack of supporting system. The business urgency-expected return matrix scoring method, which can effectively sort the importance of the process problems was also analyzed. The implementation method and key elements of process optimization were discussed, and the evaluation index system of process optimization was also constructed. The continuous customer-oriented business process optimization can effectively improve the quality of the process operation and enhance the level of enterprise operation management.

Modeling of Business Processes of Project Financing

Need of transformation of means of support of project financing for commercial banks is proved.The analysis and modeling of business processes of project management by the contextual chart and the chart of decomposition is carried out that allowed to describe the main stages of project financing.With use of tools of programming the business application of project management which will promote operational assessment on selection of introduced drafts is created.

Process Discovery and Refinement of an Enterprise Management System

The need for the analysis of modern businesses is rapidly increasing as the supporting enterprise systems generate more and more data.This data can be extremely valuable for executing organizations because the data allows constant monitoring,analyzing,and improving the underlying processes,which leads to the reduction of cost and the improvement of the quality.Process mining is a useful technique for analyzing enterprise systems by using an event log that contains behaviours.This research focuses on the process discovery and refinement using real-life event log data collected from a large multinational organization that deals with coatings and paints.By investigating and analyzing their order handling pro-cesses,this study aims at learning a model that gives insight inspection of the processes and performance analysis.Furthermore,the animation is also performed for the better inspection,diagnostics,and compliance-related questions to specify the system.The configuration of the system and the conformance checking for further enhancement is also addressed in this research.To achieve the objectives,this research uses process mining techniques,i.e.process discovery in the form of formal Petri nets models with the help of process maps,and process refinement through conformance checking and enhancement.Initially,the identified executed process is reconstructed by using the process discovery techniques.Following the reconstruction,we perform a deep analysis for the underlying process to ensure the process improvement and redesigning.Finally,some recommendations are made to improve the enterprise management system processes.

A Blockchain-Based Trust Model for Supporting Collaborative Healthcare Data Management

The development of information technology allows the collaborative business process to be run across multiple enterprises in a larger market environment.However,while collaborative business expands the realm of businesses,it also causes various hazards in collaborative Interaction,such as data falsification,inconstancy,andmisuse.To solve these issues,a blockchainbased collaborative business modeling approach was proposed and analyzed.However,the existing studies lack the blockchain risk problem-solving specification,and there is no verification technique to examine the process.Consequently,it is difficult to confirm the appropriateness of the approach.Thus,here,we propose and build a blockchain-based trust model to strengthen and verify the integrity and security of the collaborative business process;Integrity and security address the validity of collaborative interactions in terms of a trust,and we construct a blockchain pattern based on trust elements to meet the required the characteristics.Specifically,a trust model can be applied to the healthcare data-sharing process,and then the achievement of the trustbased safe data-sharing process can be proven.Our model can be used as a trust-building guidance tool or for integrity and security verification with the collaborative business process in a distributed environment with blockchain.

A Process Oriented Integration Model for Smart Health Services

Cities are facing challenges of high rise in population number and con-sequently need to be equipped with latest smart services to provide luxuries of life to its residents.Smart integrated solutions are also a need to deal with the social and environmental challenges,caused by increasing urbanization.Currently,the development of smart services’integrated network,within a city,is facing the bar-riers including;less efficient collection and sharing of data,along with inadequate collaboration of software and hardware.Aiming to resolve these issues,this paper recommended a solution for a synchronous functionality in the smart services’integration process through modeling technique.Using this integration modeling solution,atfirst,the service participants,processes and tasks of smart services are identified and then standard illustrations are developed for the better understand-ing of the integrated service group environment.Business process modeling and notation(BPMN)language based models are developed and discussed for a devised case study,to test and experiment i.e.,for remote healthcare from a smart home.The research is concluded with the integration process model application for the required data sharing among different service groups.The outcomes of the modeling are better understanding and attaining maximum automation that can be referenced and replicated.

Event-driven process execution model for process virtual machine

Current orchestration and choreography process engines only serve with dedicate process languages.To solve these problems,an Event-driven Process Execution Model(EPEM) was developed.Formalization and mapping principles of the model were presented to guarantee the correctness and efficiency for process transformation.As a case study,the EPEM descriptions of Web Services Business Process Execution Language(WS-BPEL) were represented and a Process Virtual Machine(PVM)-OncePVM was implemented in compliance with the EPEM.

Process Reengineering of Cold Chain Logistics of Agricultural Products Based on Low-carbon Economy

Through the process analysis of cold chain logistics of agricultural products,we find that cold chain logistics of agricultural products contradict the development model of low-carbon economy to some extent.We apply the development idea of low-carbon economy,introduce the thirdparty logistics companies,establish distribution center of cold chain logistics of agricultural products,and strengthen information sharing,to reengineer the process of cold chain logistics of agricultural products in China.The results show that applying low-carbon economy to process reengineering of cold chain logistics of agricultural products,has advantages of increasing added value of products,promoting scale merit and abating lag,plays a role in promoting emission reduction,high efficiency and environmental protection in the process of cold chain logistics of agricultural products in China.

Detecting Data-flow Errors Based on Petri Nets With Data Operations

In order to guarantee the correctness of business processes, not only control-flow errors but also data-flow errors should be considered. The control-flow errors mainly focus on deadlock, livelock, soundness, and so on. However, there are not too many methods for detecting data-flow errors. This paper defines Petri nets with data operations(PN-DO) that can model the operations on data such as read, write and delete. Based on PN-DO, we define some data-flow errors in this paper. We construct a reachability graph with data operations for each PN-DO, and then propose a method to reduce the reachability graph. Based on the reduced reachability graph, data-flow errors can be detected rapidly. A case study is given to illustrate the effectiveness of our methods.

A Testing Method for Web Services Composition Based on Data-Flow

This paper proposes a method of data-flow testing for Web services composition. Firstly, to facilitate data flow analysis and constraints collecting, the existing model representation of business process execution language （BPEL） is modified in company with the analysis of data dependency and an exact representation of dead path elimination （DPE） is proposed, which over-comes the difficulties brought to dataflow analysis. Then defining and using information based on data flow rules is collected by parsing BPEL and Web services description language （WSDL） documents and the def-use annotated control flow graph is created. Based on this model, data-flow anomalies which indicate potential errors can be discovered by traversing the paths of graph, and all-du-paths used in dynamic data flow testing for Web services composition are automatically generated, then testers can design the test cases according to the collected constraints for each path selected.