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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.

This research aims to elucidate why consumers decide to eat meals that seem to be higher in calories and salt, despite their goal being to consume fewer calories and sodium. Korean participants are to be used for this study. The present research further investigated the impacts of categorization and averaging bias in relation to the health halo phenomenon, specifically focusing on traditional food and textured vegetable protein (soy meat) burgers. Thus, the present research investigated how consumers' intentions contrasted with their consumption goals in food choice circumstances.

We partitioned the survey due to the COVID-19 epidemic. A single, well trained surveyor first surveyed customers at cafés in Seoul and six other Korean cities. We received 102 in-person survey replies. A total of 254 advanced degree or undergraduate students from two universities completed an online questionnaire. There are 356 responses. Two studies were conducted where participants were instructed to evaluate the perceived healthiness, calorie content, and sodium level of different food items. The specifics of each study are elucidated in the main body of the paper.

This study shows that Koreans categorize meals as virtue or vice depending on their perceived healthiness, validating the categorization effect. Furthermore, this research demonstrated that consumers' perceptions of the health benefits of traditional meals and soy meat burgers impact their categorization. Koreans also assessed the average of the vice and virtue and found vice-virtue combination meals healthier than the vice alone. This affects how calories and sodium are perceived. This study also shown that high virtue affects averaging bias more than weak virtue in meals with vice and virtue combo.

This study extended food categorization and averaging bias to non-US consumers and confirmed this contradictory meal choice is universal. Health halo also affects food health perception. The results of this study revealed that Koreans consider traditional food healthier than western junk food. Korean customers incorrectly assume soy meat burgers have fewer calories and sodium than regular burgers. Thus, this study explains Korean consumers' food health misconceptions related to paradoxical consumption.

The interpretation of any emerging form or period in art history was never a trivial task. However, in the case of digital art, technology, becoming an integral part, multiplied the complexity of describing, systematizing and evaluating it. This article investigates the most common metadata standards for the documentation of art as a broad category and suggests possible next steps toward an extended metadata standard for digital art.

Describing several techno-cultural phenomena formed in the last decade, manifesting the extendibility of digital art (its ability to be easily extended across multiple modalities), the article, at first, points to the long overdue need to re-evaluate the standards around it. Then it suggests a deeper analysis through a comparative study. In the scope of the study three artworks, The Arnolfini Portrait (Jan van Eyck), an iconic example of the early Renaissance, The World's First Collaborative Sentence (Douglas Davis), a classic example of early Internet art and Fake It Till You Make It (Maya Man), a prominent example of the blockchain art, are examined following the structure of the VRA Core 4.0 standard.

The comparative study demonstrates that digital art is more multi-semantic than traditional physical art, and requires new taxonomies as well as approaches for data acquisition.

Acknowledging that digital art simply has not yet evolved to the stage of being systematically collected by cultural institutions for documentation, curation and preservation, but otherwise, in the past few years, it has been at the front-center of social, economic and technological trends, the article suggests looking for hints on the future-proof extended metadata standard in some of those trends.

High rates of suicide and self-harm are reported in prisons in Western countries, while fewer studies exist from a non-Western context. This study aims to identify rates of suicide, non-fatal suicide attempts and self-harm in Moroccan prisons and to better understand the context, methods, tools, predictors and profile of persons engaged in the acts.

The authors report findings from a mixed-methods study carried out before an intervention project. The study consists of a systematic literature review, an analysis of suicide case files, a quantitative survey on suicide attempts and self-harm, as well as interviews and focus group discussions. The authors calculate suicide, suicide attempt and self-harm rates and present descriptive data on the incidents. The authors use regression models to explore the association between the number of incidents per individual and selected predictors, adjusting for clustering by institution.

Over a four-year period, 29 detained persons in Morocco died by suicide (average annual suicide rate 8.7 per 100,000). Most were men under the age of 30. Hanging accounted for all but one case. In one year, 230 suicide attempts were reported. Over a three-months period, 110 self-harm cases were reported from 18 institutions, cutting being the most common method. Self-harm was significantly more prevalent among persons with a life sentence or repeated incarcerations.

To make the study manageable as part of an intervention project, the authors collected data on suicides and suicide attempts from all prisons, while data on self-harm were collected from fewer prisons and over a shorter time period. The authors did not collect comparable information from detained persons who did not die by suicide, attempt suicide or self-harm. This prevented comparative analyses. Further, it is possible that self-harm cases were not reported if they did not result in serious physical injury. Data were collected by prison staff; thus, the voice of incarcerated persons is absent.

This study provided a solid basis for designing an intervention project including the development of a national prison policy and guidelines on suicides, suicide attempts and self-harm and a country-wide training program for prison staff. It also led to a better surveillance system, allowing for trend analysis and better-informed policymaking. The qualitative results helped create an understanding of how staff may trivialize self-harm. This was integrated into the training package for staff, resulting in the creation of prison staff trainers who became the strongest advocates against the notion that self-harm was best ignored.

To the best of the authors’ knowledge, this is the first published data on suicide and self-harm in Moroccan prisons. It underscores the necessity for the intervention project and gives valuable insights into suicide and self-harm in a non-Western prison context. Further research is needed to assess whether the findings are typical of the region.

In the era of artificial intelligence (AI), algorithms have gained unprecedented importance. Scientific studies have shown that algorithms are frequently mentioned in papers, making mention frequency a classical indicator of their popularity and influence. However, contemporary methods for evaluating influence tend to focus solely on individual algorithms, disregarding the collective impact resulting from the interconnectedness of these algorithms, which can provide a new way to reveal their roles and importance within algorithm clusters. This paper aims to build the co-occurrence network of algorithms in the natural language processing field based on the full-text content of academic papers and analyze the academic influence of algorithms in the group based on the features of the network.

We use deep learning models to extract algorithm entities from articles and construct the whole, cumulative and annual co-occurrence networks. We first analyze the characteristics of algorithm networks and then use various centrality metrics to obtain the score and ranking of group influence for each algorithm in the whole domain and each year. Finally, we analyze the influence evolution of different representative algorithms.

The results indicate that algorithm networks also have the characteristics of complex networks, with tight connections between nodes developing over approximately four decades. For different algorithms, algorithms that are classic, high-performing and appear at the junctions of different eras can possess high popularity, control, central position and balanced influence in the network. As an algorithm gradually diminishes its sway within the group, it typically loses its core position first, followed by a dwindling association with other algorithms.

To the best of the authors’ knowledge, this paper is the first large-scale analysis of algorithm networks. The extensive temporal coverage, spanning over four decades of academic publications, ensures the depth and integrity of the network. Our results serve as a cornerstone for constructing multifaceted networks interlinking algorithms, scholars and tasks, facilitating future exploration of their scientific roles and semantic relations.

This study aims to explore the intelligibility of communication with stakeholders as a result of accrual accounting adoption. It focuses on changes in the use of visual forms and the readability of text that occurred immediately after the adoption of accrual accounting in performance reports of Italian public universities.

The authors collect the stakeholder section of performance reports published before and after accrual accounting adoption. Then, the authors use manual and computer-assisted textual analysis. Finally, the authors explore the data using principal component analysis and qualitative comparative analysis.

This study demonstrates that switching from cash to accrual accounting provokes immediate changes in communication patterns. It confirms the significant reduction of readability and increase in visual forms after accruals accounting adoption. The results indicate that smaller universities especially put effort into increasing intelligibility while implementing a more complex accounting system. This study also finds a relation between the change in readability and the change in visual forms that are complementary, with the exception of several very large universities.

The findings underline the possibility of neutralising the adverse effects of accounting reform associated with its complexity and difficulties in understanding by the use of visual forms and attention to the document’s readability.

This paper adds a new dimension to the study of public sector accounting from the external stakeholder perspective. It provides further insight into the link between accrual accounting adoption and readability, together with the use of visual forms by universities.

This study aims to make some contribution to the process of corporate compliance governance in China.

This paper adopts qualitative method, literature research, case analysis and comparative methods to explore the Chinese compliance governance model in the field of collusive bidding crimes.

In the process of criminal prosecution of enterprises suspected of committing crimes, the judicial authorities should promote the restoration of normal production and operation of corporate enterprises by promoting the construction of corporate compliance, which is conducive to solving the difficult problem of attribution of collusive bidding crimes. In addition, corporate compliance under prosecutorial supervision is also conducive to optimizing the regulatory path of collusive bidding and achieving more effective prevention and control of unit crimes in the mode of co-regulation between the state and corporate.

Compliance governance corporate crime is at a nascent stage in China, and this study seeks to provide some reference for future compliance review governance in China through the analysis of specific business crime cases.

This study aims to explore motives behind teachers' and students' use of translanguaging and how they use it in Tanzanian public secondary school classrooms.

Data were collected using interviews and non-participant observations.

The findings indicate that translanguaging was used to facilitate content comprehension, promote classroom interaction and increase students' motivation to learn. Translanguaging was implemented using three strategies: paraphrasing an English text into Kiswahili, translating an English text into its Kiswahili equivalent and word-level translanguaging.

By highlighting the motivations for translanguaging and corresponding strategies associated with translanguaging pedagogy in the Tanzanian context, this study has significant practical implications for teachers and students to showcase their linguistic and multimodal knowledge, while fostering a safe learning space that relates to students' daily experiences.

The study offers new insights into previous research on the role of language-supportive pedagogy appropriate for teachers and students working within bi-/multilingual education settings.

This interdisciplinary study aims to analyze how service organizations communicate sustainable beliefs in their social media narratives and use them to generate brand awareness, customer recognition and ongoing demand for sustainable service.

A two-phase exploratory analysis of 10,342 tweets from 2019–2020 was conducted by sustainable global corporations to identify best practices for their social media teams operating within a service-based business model. First, the significant themes were identified using an unguided machine learning approach of three types of firms: services, goods and mixed. Next, the full set of tweets with linguistic sentiment analysis was analyzed followed by a deeper view of the services-based organizations based on their strategic focus (business-to-business [B2B] versus mixed).

The findings indicate that tweets that appear to create the highest customer engagement are characterized as having high levels of analytical language, high clout (i.e. are socially relevant), a positive tone, a high number of words and a high number of words per sentence. On the other hand, having complex language in terms of six-letter words does not seem to associate with customer engagement. The last level of analysis shows that B2B services-based corporations with positive tone and higher word count exhibit higher levels of retweets. Implications include providing rational and informational tweets to increase engagement and highlight societal relevance.

Climate change has negative consequences on human and physical capital, and ecosystems across the globe. This study provides specific recommendations for how services corporations can increase their sustainable communications and actions.

The key implication of our research is that corporations must strategically design social media narratives about climate change as part of their online branding and communications process.