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With the development of global education informatisation, the application of knowledge management system in teaching is more and more extensive, which promotes the progress of intelligent education and personalised teaching. Although the existing English teaching platform realises resource sharing and network teaching, there are still shortcomings in real-time feedback and personalised support. To solve this problem, this study proposes an English teaching assistance platform based on process management and Deep Knowledge Tracking (DKT) model. By introducing formative evaluation systems and dynamic learning data analysis, the platform provides teachers with real-time feedback to optimise teaching strategies. At the same time, the personalised practice recommendation function based on the knowledge graph can effectively improve students’ learning efficiency and knowledge mastery. The experimental results show that the Area Under Curve (AUC) value of the DKT model on six data sets is 0.83 to 0.93, which is superior to other knowledge tracking models. Moreover, the average score of students in the experimental group is 10.6 points higher than that in the blank group and 6.2 points higher than that in the control group, and the review time is reduced by 3 and 2 h. The mean square error of the platform is 0.202, and the $F$1 value is 0.93, which outperforms the traditional teaching model and significantly improves the learning effect and experience of students. Through the integration of the knowledge graph and DKT model, the platform realises the functions of dynamic learning data analysis, personalised recommendation and real-time feedback, which improves learning efficiency and optimises teaching effect. By optimizing information flow and knowledge-sharing mechanisms, in the field of public services, knowledge management helps to improve government transparency and response speed, and promote scientific and precise policy making. In addition, knowledge management also plays an important role in promoting cross-cutting cooperation, strengthening intellectual property protection and promoting sustainable development.

This study analyzes relevant contemporary software testing process models. In addition to contemporary theoretical models, the study also analyzes business software testing process models in a considerable number of software organizations. The dual (i.e. theoretical and empirical) analysis of the testing process aims to provide a basis for a testing process model design which is specific to testing business software in small and medium software organizations. The empirical study was conducted by a survey research strategy in 24 software organizations. In order to gather detailed information on the testing process, an interview was conducted on a purpose-selected sample of four organizations. The gathered data were processed by quantitative and qualitative data analysis. The results of theoretical and empirical research were used as a basis for attaining the study’s desired outcome: the business software testing process-based model which was graphically presented in BPMN 2.0 notation and described according to the ISO/IEC TR 24774 standard for process description in systems and software engineering. The combination of the graphic representation of the model and its description in compliance with the process description is a proven method in process management, which should enable easier understanding, and thus the implementation of the model in small and medium software organizations.

Self-organization is an important factor in the processes of quality management systems. The advantage of self-organization processes is that these processes have a certain stability and adaptability to the environment. The knowledge of fundamental regularities of self-organization allows the designing of active artificial environments, activities of which can result in the formation of desired structures. For example, changes in customers’ requirements can make necessary additional professional development for employees, introduction of benchmarking procedures etc. Self-organization, enables the process ability to enhance its structure and implementation technology depending on the environment. Formally, self-organization model is described as follows. Quality management process is represented as a model of a complex system with input values (such as requirements to the quality level $(Q)$ and managing actions $(B)$) and output signals (such as multiple factors of a process quality $(Y)$). Development of quality management system processes in the mechanical engineering industry (complication of a structure or production technology, etc.) is realized considerably by using self-organization principles. By analyzing the causes of self-organizational processes development, we can conclude that a fundamental factor for that process is the desire to improve the competitiveness of an organization which implies the development of effective quality management system.

Standards like SOAP, WSDL, and UDDI facilitate the proliferation of services. Based on these technologies, processes are a means to combine services to applications and to provide new value-added services. For large information systems, a centralized process engine is no longer appropriate due to limited scalability. Instead, in this paper, we propose a distributed and decentralized process engine that routes process instances directly from one peer to the next. Such a peer-to-peer process execution promises good scalability characteristics since it is able to dynamically balance the load of processes and services among all available service providers. Therefore, navigation costs only accumulate on peers that are directly involved in the execution. However, this requires sophisticated strategies for the replication of meta-data for peer-to-peer process execution. Especially, replication mechanisms should avoid frequent accesses to global information repositories. In our system, called OSIRIS (Open Service Infrastructure for Reliable and Integrated Process Support), we deploy a publish/subscribe-based replication scheme together with freshness predicates to significantly reduce replication costs. This way, OSIRIS can support process-based applications in a dynamically evolving system without limiting scalability and correctness. Experiments have shown very promising results with respect to scalability. In addition, OSIRIS provides a flexible infrastructure that can be extended seamlessly in a modular way. This paper demonstrates the extension towards distributed concurrency control.

Most of today’s approaches to business process engineering (also called business process management) start from an activity-centered perspective. They describe activities to be carried out within a business process and their relationships, but they usually pay little attention to the objects manipulated within processes. In this article, we discuss an approach to business process modeling, model analysis, and business process enaction (also called workflow management) which is based on data modeling, activity modeling, and organization modeling. In fact, the ℒeu approach to business process management considers data models (describing types of objects to be manipulated in a business process and their relationships), activity models (describing activities to be carried out in a business process), and organization models (describing organizational entities involved in a business process) as separate, but equally important, facets of business processes.

In this article, agent based process management model is proposed, which is for the process management of knowledge worker and service workers in order to establish the basis for the new knowledge management system. In this article, we applied several methods from 6-Sigma and personal software process for personal process definition, process execution and process measurement. This study attempts to improve the process execution accuracy through process visualisation and standardisation and to accumulate the base data to improve the process through measuring the process execution. We proposed guidelines and detail procedures for developing three advisor agents for guiding the process definition, process execution and process measurement. We showed the simple case study applied our guidelines.

There are three distinct functions in the product realization chain — product design, process design, and process execution; thus there are two interfaces (product design — process design; process design — process execution) rather than one (product-manufacturing). Case studies of four organizations manufacturing high-tech products in New Zealand are explored to study the organization of process design functions and success strategies. Similarities in structuring, relationships between functional groups, and the methods for product and process design implementation are investigated. De-coupling of process design functions occurs best with high volume production with stable process technology — an infrequent situation with high-tech NZ manufacturers.

The need for effective and efficient Product Innovation (PI) is a great challenge for organisations in today’s hypercompetitive global markets. Many research studies addressed problems/obstacles to successful PI from various perspectives. Many other studies proposed factors to help companies mitigate such problems. Here, the primary objective is to propose an integrated model, to empirically test this model, and get insights about which factors, if managed appropriately, will help reduce the obstacles to PI in practice. A questionnaire was developed, pilot tested, and used to collect data from 47 PI managers. The results support the theoretical importance of a formal PI process, characteristics of the company environment, and the availability of specific resources as important factors to reduce obstacles to company PI. Based on the results recommendations are made to practitioners and researchers in this important area.

One may expect the Internet to evolve from being information centric to knowledge centric. This paper introduces the concept of a Knowledge Society Operating System (KSOS) that allows users to form knowledge societies in which members can search, create, manipulate and connect geographically distributed knowledge resources (including data, documents, tools, people, devices, etc.) based on semantics (“meaning”, “intention”) in order to solve problems of mutual interest. Built on top of the current Internet infrastructure, a KSOS can take advantage of existing resources to enable the use of applications or services through a web browser. This paper discusses some crucial aspects of a KSOS.

Internet of Things-aware process execution imposes new requirements on process modeling that are outside the scope of current modeling languages. Internet of Things (IoT) devices may vanish, appear or stay unknown during process execution, which renders process resource allocation at design time infeasible. Devices’ capabilities are often only available in a particular real-world context at runtime. This is not considered by current approaches that use services for encapsulating device functionality. We propose a novel approach to enable both service discovery and invocation for IoT-aware processes based on users’ goals that are defined as part of a process. We apply the Tropos goal modeling methodology to represent the dependencies between these goals and IoT device capabilities. Furthermore, we present a Semantic Access Layer (SAL) to transform these goals into service invocations using generated SPARQL queries. The SAL executes the queries on a knowledge base representing runtime domain knowledge about IoT services, their capabilities, and context. As a result, it invokes the identified IoT services and transfers the responses back to the process engine. The evaluation of our approach within several Smart Home scenarios shows an increase of flexibility and separation of concerns for scalable, IoT-aware process execution.

The need for effective and efficient product innovation (PI) is a great challenge for organisations in today’s hypercompetitive global markets. Many research studies addressed problems/obstacles to successful PI from various perspectives. Many other - studies proposed factors to help companies mitigate such problems. Here, the primary objective is to propose an integrated model, to empirically test this model, and get insights about which factors, if managed appropriately, will help reduce the obstacles to PI in practice. A questionnaire was developed, pilot tested, and used to collect data from 47 PI managers. The results support the theoretical importance of a formal PI process, characteristics of the company environment, and the availability of specific resources as important factors to reduce obstacles to company PI. Based on the results recommendations are made to practitioners and researchers in this important area.

The main purpose of the presented research is to contribute to a better understanding of business process reengineering (BPR), supported with performance measurement (PM) indicators with the purpose to improve company operations efficiency. Existing literature on the subject warns about deficiencies in the concept of BPR, which can be extremely efficient with its radical workings. The concept of BPR should be studied in connection with the logical supplementary areas: manufacturing strategy and, on the other hand, performance indicators, meant for selected manufacturing strategy and BPR performance verification. BPR and PM literature is based primarily on case studies and there is a lack of rigorous wide-ranging empirical research covering all its aspects. This chapter presents the results of a survey research carried out in 73 medium- and large-sized Slovenian manufacturing companies. Seven crucial areas were identified based on a synthesis of PM literature, which must be practiced to achieve effective operations: cost, quality, time, flexibility, reliability, customer satisfaction, and human resources. Variables have been constructed within these areas, using Likert scales, and statistical validity, and reliability analyses.

In order to overcome the difficulties of inadequate ability of knowledge reuse in the maintenance, repair and overhaul of the aerospace products, this paper focused on the key technology of knowledge actively pushing on repair process management and knowledge reuse, provided data source which suit the repair data acquisition for repair knowledge learning. Furthermore, repair knowledge is mined from repair data with Markov model, formed the knowledge model based on the maintenance data sequence. At last, knowledge actively pushing system with the knowledge demand of the repair node is build, the traditional workflow engine is also rebuild, which realized the extensible mechanism of knowledge files, and pushed knowledge actively according to the repair node requirement.