Transferring architectural management into practice： A taxonomy framework

This research aimed to develop a unique framework to help architects understand and apply architectural management （AM） in their practices. A comprehensive literature review identified several components belonging to different specialist fields. A pragmatic methodology for developing the framework was adopted by combining the methodology of Japareen for building conceptual frameworks with the Concept Mapping and Qualitative Met-Synthesis techniques. The resulting framework underwent a series of testing stages aimed at refining the framework further. The testing process targeted two groups （researchers and professionals） by adopting a mixed method approach, which included a facilitated workshop, interviews, and a questionnaire survey. The feedback from the testing phase was used to create the final AM Taxonomy Framework （AMTF）, and served as an original and practical guide for practitioners, further extending their understanding of AM. Further validation and refinement are planned in the long term by applying the framework to selected architectural practices.

ANALYSIS TOOL OF REQUIREMENT AND ARCHITECTURE MANAGEMENT IN COMPLEX SYSTEM

To facilitate system integration and evolution, modeling of complex systems requires a complementary management of system requirements and the architecture. Software tools are essential to support the above management effectively. The envisaged analysis tool for requirement and architecture management （ATRAM） is used to address the following 3 issues： （1） system requirements; （2） architecture presentation （modeling）; （3） representation （marking-up） and traceability between the components of both sides. In ATRAM, a set of analysis tools is proposed. It includes a tool assisting in the generation/development of requirement documents pertaining to the architecture of composed systems, and an XML based tool for interoperability checking. It is useful for analyzing the influences of the change on enterprise system requirements or the architecture.

Research on logistics domain-oriented cloud resource management model and architecture

To address the challenges posed by resource shortage or surplus to enterprises productivity,Internet platforms have been widely used,which can balance shortage and surplus in broader environments. However,the existing resource management models lack openness,sharing ability and scalability,which make it difficult for many heterogeneous resources to co-exist in the same system. It is also difficult to resolve the conflicts between distributed self-management and centralized scheduling in the system. This paper analyzes the characteristics of resources in the distributed environment and proposes a new resource management architecture by considering the resource aggregation capacity of cloud computing. The architecture includes a universal resource scheduling optimization model which has been applied successfully in double-district multi-ship-scheduling multi-container-yard empty containers transporting of international shipping logistics. Applications in all these domains prove that this new resource management architecture is feasible and can achieve the expected effect.

Network Meets ChatGPT:Intent Autonomous Management,Control and Operation

Telecommunication has undergone significant transformations due to the continuous advancements in internet technology,mobile devices,competitive pricing,and changing customer preferences.Specifically,the most recent iteration of OpenAI’s large language model chat generative pre-trained transformer(ChatGPT)has the potential to propel innovation and bolster operational performance in the telecommunications sector.Nowadays,the exploration of network resource management,control,and operation is still in the initial stage.In this paper,we propose a novel network artificial intelligence architecture named language model for network traffic(NetLM),a large language model based on a transformer designed to understand sequence structures in the network packet data and capture their underlying dynamics.The continual convergence of knowledge space and artificial intelligence(AI)technologies constitutes the core of intelligent network management and control.Multi-modal representation learning is used to unify the multi-modal information of network indicator data,traffic data,and text data into the same feature space.Furthermore,a NetLM-based control policy generation framework is proposed to refine intent incrementally through different abstraction levels.Finally,some potential cases are provided that NetLM can benefit the telecom industry.

Semantics-oriented approach for information interoperability and governance:towards user-centric enterprise architecture management

Enterprise architecture (EA) efforts focus on business, technology, data, and application architecture, and their integration. However, less attention has been given to one of the most critical EA elements, i.e., users (EA audiences). As a result, existing EA management systems (EAMS) have become old, large, content-centric document-repositories that are unable to provide meaningful information of use to the enterprise users and aligned with their needs and functional scope. We argue that a semantic technology based mechanism focusing on enterprise information and user-centricity has the potential to solve this problem. In this context, we present a novel ontology-based strategy named the user-centric semantics-oriented EA (U-SEA) model. Based on this model, we have developed a user-centric semantics-oriented enterprise architecture management (U-SEAM) system. Our approach is generic enough to be used in a wide variety of user-centric EAM applications. The results obtained show computational feasibility to integrate and govern enterprise information and to reduce complexity with respect to interoperability between enterprise information and users.

Marginalization and invasion of architects＇ role on house projects： Institutional intervention inadequacy and super wicked problems

The design and construction of houses normally require an architect＇s input. However, architects are increasingly being marginalized in these projects, and their roles are constantly being invaded by others. Despite repeated institutional interventions toward remedying this phenomenon, signs are not abating. This article examines the complexity of this phenomenon to explain the inadequacy of institutional interventions to address the problem. This article conceptualizes the phenomenon of marginalization and role invasion as a super wicked problem with six key features. First, the problem has a difficult definition. Second, the solution involves a large structural and economic burden. Third, time is of the essence. Fourth, multiple stakeholders attempting to solve the problem are part of the cause. Fifth, institutional interventions addressing the issue are weak or ill-equipped. Sixth, institutional interventions discount the future irrationally. The implications of this conceptualization for institutional intervention and research are discussed.