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The compliance checking of Building Information Modeling (BIM) models is crucial throughout the lifecycle of construction. The increasing amount and complexity of information carried by BIM models have made compliance checking more challenging, and manual methods are prone to errors. Therefore, this study aims to propose an integrative conceptual framework for automated compliance checking of BIM models, allowing for the identification of errors within BIM models.

This study first analyzed the typical building standards in the field of architecture and fire protection, and then the ontology of these elements is developed. Based on this, a building standard corpus is built, and deep learning models are trained to automatically label the building standard texts. The Neo4j is utilized for knowledge graph construction and storage, and a data extraction method based on the Dynamo is designed to obtain checking data files. After that, a matching algorithm is devised to express the logical rules of knowledge graph triples, resulting in automated compliance checking for BIM models.

Case validation results showed that this theoretical framework can achieve the automatic construction of domain knowledge graphs and automatic checking of BIM model compliance. Compared with traditional methods, this method has a higher degree of automation and portability.

This study introduces knowledge graphs and natural language processing technology into the field of BIM model checking and completes the automated process of constructing domain knowledge graphs and checking BIM model data. The validation of its functionality and usability through two case studies on a self-developed BIM checking platform.

Neutral format translators such as STEP and IGES have been used to exchange CAD model between the various CAD systems in the product development process. But imperfect interoperability imposes costs on the industry due to higher costs of design and production and slower implementation of design changes. In this paper, we propose a procedural approach to inspect the CAD model's errors that occur in a neutral format. We employed two separate inspection processes for checking CAD model errors without wasting excessive resources: the topological data structure and the geometrical data structure. We developed the 3D CAD model inspection system to check the topological and geometrical errors and applied it to case study. An inspection record can be edited in HTML, and thus can be shared by any designer at any time.

Business process (BP) reengineering is defined as reinventing BPs either structurally or technically to achieve dramatic improvements in performance. In any business process reengineering (BPR) project, process modeling is used to reason about problems found in existing (as-is) process and helps to design target (to-be) process. BP model notation is a widely accepted standard for process modeling. “Expressiveness” and “missing formal semantics” are two problems reported to its modeling practices. In existing studies, solutions to these problems are also proposed but still have certain limitations. The paper aims to discuss this issue.

In proposed methodology, a meta-model is formally defined that is composed of commonly used modeling elements and their well-formedness rules to check for syntactic and structural correctness of process models. Proposed solution also check semantics of process models and allows to compare as-is and to-be process models for gap identification which is another important aspect of BPR. To achieve the first goal, Z specification is used to provide formal specifications of modeling constructs and their rules and Z3 (an SMT solver) is used for comparisons and verifying properties.

Proposed method addresses both “expressiveness” and “missing formal semantics” of BPR models. The results of its evaluation clearly indicate that using formally specified meta-model, BPR model is syntactically and structurally correct. Moreover, formal modeling of BPs in Z3 helped to compare processes and to check control flow properties.

Although the proposed method is tested on an example that is widely used in BPR literature, the example is only covering modeling elements which are part of the proposed subset and are reported in literature as frequently used modeling elements. A separate detailed study is required to test it on more complex systems.

Specifying process models using Z specification and Z3 solver requires certain expertise.

The proposed method adds value to BPR body of knowledge as it proposes a method to ensure structural and syntactic correctness of models, highlighting the importance of verifying run time properties and providing a direction toward comparing process models for gap analysis.

The purpose of this paper is to develop new simple logics and translations for hierarchical model checking. Hierarchical model checking is a model-checking paradigm that can appropriately verify systems with hierarchical information and structures.

In this study, logics and translations for hierarchical model checking are developed based on linear-time temporal logic (LTL), computation-tree logic (CTL) and full computation-tree logic (CTL*). A sequential linear-time temporal logic (sLTL), a sequential computation-tree logic (sCTL), and a sequential full computation-tree logic (sCTL*), which can suitably represent hierarchical information and structures, are developed by extending LTL, CTL and CTL*, respectively. Translations from sLTL, sCTL and sCTL* into LTL, CTL and CTL*, respectively, are defined, and theorems for embedding sLTL, sCTL and sCTL* into LTL, CTL and CTL*, respectively, are proved using these translations.

These embedding theorems allow us to reuse the standard LTL-, CTL-, and CTL*-based model-checking algorithms to verify hierarchical systems that are modeled and specified by sLTL, sCTL and sCTL*.

The new logics sLTL, sCTL and sCTL* and their translations are developed, and some illustrative examples of hierarchical model checking are presented based on these logics and translations.

The purpose of this paper is to present a method that addresses the data sparsity problem in points of interest (POI) recommendation by introducing spatiotemporal context features based on location-based social network (LBSN) data. The objective is to improve the accuracy and effectiveness of POI recommendations by considering both spatial and temporal aspects.

To achieve this, the paper introduces a model that integrates the spatiotemporal context of POI records and spatiotemporal transition learning. The model uses graph convolutional embedding to embed spatiotemporal context information into feature vectors. Additionally, a recurrent neural network is used to represent the transitions of spatiotemporal context, effectively capturing the user’s spatiotemporal context and its changing trends. The proposed method combines long-term user preferences modeling with spatiotemporal context modeling to achieve POI recommendations based on a joint representation and transition of spatiotemporal context.

Experimental results demonstrate that the proposed method outperforms existing methods. By incorporating spatiotemporal context features, the approach addresses the issue of incomplete modeling of spatiotemporal context features in POI recommendations. This leads to improved recommendation accuracy and alleviation of the data sparsity problem.

The research has practical implications for enhancing the recommendation systems used in various location-based applications. By incorporating spatiotemporal context, the proposed method can provide more relevant and personalized recommendations, improving the user experience and satisfaction.

The paper’s contribution lies in the incorporation of spatiotemporal context features into POI records, considering the joint representation and transition of spatiotemporal context. This novel approach fills the gap left by existing methods that typically separate spatial and temporal modeling. The research provides valuable insights into improving the effectiveness of POI recommendation systems by leveraging spatiotemporal information.

While there is increasing interest in implementing drug checking within overdose prevention, we must also consider how to scale-up these responses so that they have significant reach and impact for people navigating the unpredictable and increasingly complex drug supplies linked to overdose. The purpose of this paper is to present a distributed model of community drug checking that addresses multiple barriers to increasing the reach of drug checking as a response to the illicit drug overdose crisis.

A detailed description of the key components of a distributed model of community drug checking is provided. This includes an integrated software platform that links a multi-instrument, multi-site service design with online service options, a foundational database that provides storage and reporting functions and a community of practice to facilitate engagement and capacity building.

The distributed model diminishes the need for technicians at multiple sites while still providing point-of-care results with local harm reduction engagement and access to confirmatory testing online and in localized reporting. It also reduces the need for training in the technical components of drug checking (e.g. interpreting spectra) for harm reduction workers. Moreover, its real-time reporting capability keeps communities informed about the crisis. Sites are additionally supported by a community of practice.

This paper presents innovations in drug checking technologies and service design that attempt to overcome current financial and technical barriers towards scaling-up services to a more equitable and impactful level and effectively linking multiple urban and rural communities to report concentration levels for substances most linked to overdose.

The paper proposes that improvements in the productivity of process technology can be achieved by analyzing and instituting changes in the rules and methods through which work is organized. The implementation of information‐based process technology in a bank’s check processing system provides the context for the study. A simulation approach is used to assess the benefits of introducing alternative workflow scheduling rules after implementation of the new technology. Results from a hypothetical setting, using data from an actual check processing center, demonstrate the cost advantages of introducing a priority‐based scheduling rule. The implications and problems associated with practical implementation are discussed.

This study aims to describe the behavior of blocks in the system under consideration using systems modeling language (SysML) state machine diagrams. In this paper, formalization and model checking for SysML state machine diagrams have been investigated.

The work by Zhang and Liu (2010) proposed a formalization of SysML state machine diagrams in which the diagrams were translated into CSP# processes that could be verified by the state-of-the-art model checker PAT. In this paper, several modifications have been made and new rules have been added to the translation described in that work.

First, three translation rules were modified, which apparently are inappropriately defined according to the SysML definition of state machine diagrams. Next, we add new translation rules for two components of the diagrams – junction and choice pseudostates – which have not been dealt with previously. Further, we are implementing the automatic translation system on a web-based model-driven development tool, which reflects on our translation rules.

As the contribution of this work, more reasonable verification results for more general SysML state machine diagrams can be achieved.

The life span of an aircraft is usually around 30 years in the commercial aviation industry. During this time span, aircraft needs maintenance to stay in service. The cost of maintenance, repair and overhaul (MRO) activities in its pure nature is a significant portion of operations, accounting around 10 percent of all cost drivers. The purpose of this paper is to design/develop and critically assess a comprehensive model of operations at Turkish Technic – the MRO department of Turkish Airlines.

A comprehensive systems dynamics model is designed and developed to holistically represent and critically assess the different facets of MRO operations to help in analyzing various decision scenarios at Turkish Airlines.

The developed system dynamics (SD) model presented unique opportunities to test various MRO operations’ work load and aircraft fleet expansion policy alternatives. The model can also be used as a “learning laboratory” by altering various system parameters and testing different policies. The case study results suggested that MRO operations have a direct impact on the available number of airworthy aircrafts and hence, the usable fleet seat capacity; to sustain a profitable airline fleet, the airline companies should take into account the unique characteristics/needs of MRO operations for both existing and new/prospective aircrafts.

There are several SD studies in the literature focusing on the airline industry, but the MRO operations are virtually neglected in them. Hence, the proposed SD model contributed to the extant literature. The value of the developed model stems from its potential use in the critical analysis of decision scenarios as well as being leveraged as a training/learning laboratory.

This paper aims at supporting business process designers in modelling collaborative scenarios in terms of hierarchical BPMN collaboration diagrams, to enforce consistency among different hierarchical levels.

The proposed approach is based on a set of guidelines to apply during the modelling of hierarchical diagrams. These guidelines address consistency issues related to the hiding capability provided by sub-process and call activity elements, which may obscure behaviours at inner levels, especially exchange of messages, that are inconsistent with those in other hierarchical levels. A laboratory experience validates the guidelines' effectiveness.

The paper points out the issues of hierarchical diagrams, and the lack of support in this context from the existing BPMN modelling tools. Moreover, through a laboratory experience, the paper shows the benefits carried by the proposed guidelines concerning the quality of the modelled diagrams.

The proposed guidelines have been implemented in a consistency checking tool that avoids consistency errors during the modelling activity. To foster its usage, the tool has been integrated into the Eclipse BPMN modelling environment.

The paper, employing consistency guidelines, provides a novel solution to the weaknesses of hierarchical modelling.