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Defects in concrete surfaces are inevitably recurring during construction, which needs to be checked and accepted during construction and completion. Traditional manual inspection of surface defects requires inspectors to judge, evaluate and make decisions, which requires sufficient experience and is time-consuming and labor-intensive, and the expertise cannot be effectively preserved and transferred. In addition, the evaluation standards of different inspectors are not identical, which may lead to cause discrepancies in inspection results. Although computer vision can achieve defect recognition, there is a gap between the low-level semantics acquired by computer vision and the high-level semantics that humans understand from images. Therefore, computer vision and ontology are combined to achieve intelligent evaluation and decision-making and to bridge the above gap.

Combining ontology and computer vision, this paper establishes an evaluation and decision-making framework for concrete surface quality. By establishing concrete surface quality ontology model and defect identification quantification model, ontology reasoning technology is used to realize concrete surface quality evaluation and decision-making.

Computer vision can identify and quantify defects, obtain low-level image semantics, and ontology can structurally express expert knowledge in the field of defects. This proposed framework can automatically identify and quantify defects, and infer the causes, responsibility, severity and repair methods of defects. Through case analysis of various scenarios, the proposed evaluation and decision-making framework is feasible.

This paper establishes an evaluation and decision-making framework for concrete surface quality, so as to improve the standardization and intelligence of surface defect inspection and potentially provide reusable knowledge for inspecting concrete surface quality. The research results in this paper can be used to detect the concrete surface quality, reduce the subjectivity of evaluation and improve the inspection efficiency. In addition, the proposed framework enriches the application scenarios of ontology and computer vision, and to a certain extent bridges the gap between the image features extracted by computer vision and the information that people obtain from images.

A mixed-method study was performed to determine the impact of integrating systems thinking (ST) into an electronic learning module for junior high school teachers in the Philippines. The study aims to assess how an ST approach to pedagogy compared against a conventional approach in terms of contribution to the participants’ global climate change content knowledge, holistic thinking and depth and accuracy of knowledge and reasoning.

The study implemented e-learning modules using an ST approach versus a conventional approach in teaching climate science to junior high school teachers. The paper presents quantitative data obtained from pre and posttests results of the 20 teacher-participants and qualitative data obtained during the focus-group discussion (FGD) after the implementation of the study.

The results from the statistical analysis indicated that the ST group obtained a significant increase in their assessment scores compared to the non-ST group, according to predetermined criteria. Content knowledge, depth and accuracy of knowledge and reasoning increased the most. The participants mentioned during the FGD that the module helped deepen their understanding of climate change.

The study was limited to 20 teacher-participants, but it has relevance for public school teachers in the country given that participants had raised concerns regarding the lack of training in their schools for teaching climate science. They admitted that they lacked critical information to include in climate change topics in their classes.

This paper shows how the ST approach can be used to teach climate change to junior high students. The e-learning module can provide teachers with better understanding, knowledge and reasoning to teach climate change to high school students more effectively.

Currently, the Tang tomb mural cultural relic resources are presented in a multi-source and heterogeneous manner, with a lack of effective organization and sharing between resources. Therefore, this study aims to propose a multidimensional knowledge discovery solution for Tang tomb mural cultural relic resources.

Taking the Tang tomb murals collected by the Shaanxi History Museum as an example, based on clarifying the relevant concepts of Tang tomb mural resources and considering both dynamic and static dimensions, a top-down approach was adopted to first construct an ontology model of Tang tomb mural type cultural relics resources. Then, the actual case data was imported into the Neo4J graph database according to the defined pattern hierarchy to complete the static organization of knowledge, and presented in a multimodal form in knowledge reasoning and retrieval. In addition, geographic information system (GIS) technology is used to dynamically display the spatiotemporal distribution of Tang tomb mural resources, and the distribution trend is analysed from a digital humanistic perspective.

The multi-dimensional knowledge discovery of Tang tomb mural cultural relics resources can help establish the correlation and spatiotemporal relationship between resources, providing support for semantic retrieval and navigation, knowledge discovery and visualization and so on.

This study takes the murals in the collection of the Shaanxi History Museum as an example, revealing potential knowledge associations in a static and intelligent way, achieving knowledge discovery and management of Tang tomb murals, and dynamically presents the spatial distribution of Tang tomb murals through GIS technology, meeting the knowledge presentation needs of different users and opening up new ideas for the study of Tang tomb murals.

There is strong excitement during Ponzi schemes and financial bubble periods. This emotion causes investors to turn to “unknown and new investment instruments”. This study, the factors that made “unknown and new investment instruments” preferable to “known and experienced investment instruments” were investigated.

It was taken into account unconscious like phantasy, emotional like emotional intelligence, both affective and cognitive like financial literacy and subjective beliefs like trust and overconfidence. In addition, risk preferences were measured with four different risk variables. In this context, data were collected by online survey method between November 2020 and May 2021 with convenience sampling. First, the data were collected from 832 participants in the pilot study. Additional data were also collected using convenience sampling and online surveys, and a total of 1,692 participants were obtained. Data were analyzed using Statistical Package for the Social Sciences (SPSS) 25 and AMOS 24.

As a result of the analyses made, the variables that lead investors to choose “unknown and new investment instruments” were determined as risky investment intention, phantasy, risk taking/risk avoidance, confidence, risk tolerance and subjective financial literacy. Trust and risk perception have a very weak effect on preferences. However, no effect of emotional intelligence and objective financial literacy was detected. In addition, a moderately positive and significant relationship was found between objective and subjective financial literacy. Subjective financial literacy was found to have a strong and significant relationship with emotional intelligence, confidence, trust, risky investment intention and phantasy.

This study investigates the factors underlying individuals' investment preferences from a broad perspective. We think that this study is unique in this structure and wide variables. We believe that the findings obtained in this manner are unique to both academics and practitioners. We also believe that the findings of the study will make an important contribution to understanding participation behavior in various Ponzi schemes and financial bubbles.

This study aims to adopt the microfoundation perspective to investigate undesirable knowledge rejection by individuals in organizations in the context of counterproductive knowledge behavior (CKB). The paper advances a conceptual framework of the conditions of knowledge rejection by individuals and their respective knowledge rejection behavior types.

This study reviews the limited literature on knowledge rejection and outline a set of antecedents leading to rejecting knowledge as well as a set of different types of knowledge rejection behaviors. This study reviews and synthesizes articles on knowledge rejection from a microfoundation perspective.

The proposed conceptual framework specifies four particular conditions for knowledge rejection and outlines four respective knowledge rejection behavior types resulting from these conditions. Recipients’ lack of capacity leads to ineptitude, lack of motivation leads to dismissal of knowledge, lack of alignment with the source leads to disruption and doubts about the validity of external knowledge lead to resistance. The authors treat these behaviors as variants of CKB, as they can hinder the productive use of knowledge resources in the organization.

Further investigation of both knowledge rejection causes and the resulting knowledge rejection behaviors will ensure a more thorough grasp of the relationships between them, both in terms of the inherent nature of these relationships and their dynamics that would likely be context-sensitive. Although this study focuses only on the individual level, future studies can conduct multi-level analyses of undesirable knowledge rejection, including team and organizational levels.

Practitioners can use the framework to identify, diagnose and manage knowledge rejection more meaningfully, accurately and purposefully in their organizations. This study offers valuable insights for managers facing undesirable knowledge rejection, and provides recommendations on how to address this behavior, improves the constructive use of knowledge resources and the effectiveness of knowledge processes in their organizations. Managers should be aware of undesirable knowledge rejection, its potential cost or concealed cost to their organizations and develop strategies to reduce or prevent it.

The paper contributes toward understanding the relatively neglected topic of knowledge rejection in the knowledge management field and offers a new way of conceptualizing the phenomenon. It proposes that there are two types of knowledge rejection – undesirable and desirable – and advances a more precise and up-to-date definition of undesirable knowledge rejection. Responding to calls for more research on CKBs, the study examines a hitherto unresearched behavior of knowledge rejection and provides a foundation for further study in this area.

The purpose of this study is to examine the knowledge gap hypothesis in the context of smartphone use for news to understand whether mobile news consumption could bridge or widen the knowledge gap between people of higher and lower socioeconomic status (SES).

The authors examine how smartphone news consumption is associated with the knowledge gap hypothesis by analyzing a survey dataset from Hong Kong. This study focuses specifically on a moderated mediation model in which the indirect effect of mobile news consumption on political knowledge via discussion network heterogeneity is contingent on level of education.

Smartphone use for news/information was positively associated with level of discussion network heterogeneity. The indirect effect of smartphone news use on political knowledge via discussion network heterogeneity was stronger for those with lower levels of education.

This study advances the understanding of the role of smartphone use in contributing to the functioning of deliberative democracy as this use enhances discussion network heterogeneity and general levels of political knowledge. Moreover, our study contributes to the literature on the knowledge gap by not only examining the relationship between smartphone use, discussion heterogeneity, and political knowledge but also taking into consideration individual levels of education.

Drawing on the social cognitive model of career self-management (CSM model) and deep learning theory, the authors' study aims to investigate the effect of knowledge sharing on career adaptability and explore how and when this effect occurs. The authors proposed a moderated sequential-mediation model linking knowledge sharing, knowledge depth, self-efficacy and career adaptability, moderated by reflective thinking.

The authors used a field survey involving 611 employees working in different enterprises in China to test the authors' predictions. For supplementary validation, the authors conducted a scenario-based experiment with a distinct sample of 148 employees from Chinese enterprises. The authors used hierarchical regression analysis, ANOVA analysis and moderated sequential-mediation analysis to test the hypotheses.

The results indicated a positive effect of knowledge sharing on career adaptability, sequentially mediated through knowledge depth and self-efficacy. Additionally, reflective thinking strengthened the positive effect of knowledge sharing on knowledge depth and further moderated the sequential mediating effect.

Previous research has predominantly focused on the perspective that individuals act as “recipients” from the environment in developing career adaptability. Instead, the authors adopt a “giving” perspective by investigating the influence of knowledge sharing on career adaptability, which advances the existing knowledge on the predictors of career adaptability.

This study aims to adopt a systematic review approach to examine the existing literature on law and LLMs.It involves analyzing and synthesizing relevant research papers, reports and scholarly articles that discuss the use of LLMs in the legal domain. The review encompasses various aspects, including an analysis of LLMs, legal natural language processing (NLP), model tuning techniques, data processing strategies and frameworks for addressing the challenges associated with legal question-and-answer (Q&A) systems. Additionally, the study explores potential applications and services that can benefit from the integration of LLMs in the field of intelligent justice.

This paper surveys the state-of-the-art research on law LLMs and their application in the field of intelligent justice. The study aims to identify the challenges associated with developing Q&A systems based on LLMs and explores potential directions for future research and development. The ultimate goal is to contribute to the advancement of intelligent justice by effectively leveraging LLMs.

To effectively apply a law LLM, systematic research on LLM, legal NLP and model adjustment technology is required.

This study contributes to the field of intelligent justice by providing a comprehensive review of the current state of research on law LLMs.

The purpose of this study is to gain insight into the dynamics and considerations of professionals regarding the sharing of tacit, personal knowledge in their practice.

Adopting a social-constructivist ontology, the qualitative design deploys semi-structured interviews and focus groups. Data were coded, and analysed through interrelating and reasoning.

Personal knowledge is difficult to share precisely, but can be shared to some extent using reflection and stories. Knowledge also provides a position and professional agency, emphasising boundaries and impacting the decisions on interaction and sharing. As such, professional commitment is vulnerable and contextual and, by extension, material becomes part of this interplay of professional practice and collaborative development.

Findings imply that exchange and use of knowledge and material present in organisations are impacted by individual professionals’ autonomy and decisions, which consequently impact on employees’ practice. This calls for research that focuses on individual factors such as autonomy, professionalism and attitudes in addition to organisational and facilitative matters.

Stimulating professional commitment and interpersonal learning is a matter of valuing personal knowledge and practice to avoid protectionism, boundaries and segregated agency. Management and professionals should consider how and why individuals exchange their personal knowledge, paying attention to social structures and individuals’ voices and objectives in forming communities.

This study combines the concept of tacit knowledge with the younger field of practice theory. By connecting personal knowledge to practice, it extends agency to the material world and offers a more individual perspective to knowledge sharing in and between entities.

This study aims to investigate the concept of “practical wisdom” which may be defined as the ability to effectively manage one’s rational knowledge and to read and respond appropriately to the interplay of other people's emotions and one's own and their values. The aims of this study also are (1) to investigate the relationship between the spiritual, emotional and rational capacities which underpin practical wisdom and (2) to analyse the relationship between the practical wisdom co-created in and between individuals through these three capacities.

This study adopts a case study methodology by considering the experience provided by a group of hikers who organized a trip to cross the island of Gran Canarias and its natural parks.

This study proposes that the presence of spiritual, emotional or rational capacities can boost individual self-awareness, self-control and empathy, which can help workers in general and knowledge workers, in particular, more effectively tackle difficult situations, remain calm and collectively develop and enact appropriate responses to these situations. Therefore, results show that the concept of practical wisdom allows for the identification of both the nature of the capacities that contribute to the effective handling of difficult situations and them and the balance that needs to be developed between them.

For knowledge workers, the study provides a framework and an explanatory framework to help them understand how rational, spiritual and emotional capacities both interact and are operationalized to tackle difficult problems. Furthermore, it enables them to identify situations where success to consider such interactions, leads to develop and implement appropriate responses to such situations.

A proper balance of emotional, rational and spiritual capacities may enable people to have a more holistic vision of difficult situations, allowing the finding of appropriate solutions to complex problems (i.e. practical wisdom). This study contributes to strengthening knowledge workers' perception and understanding of the links between the knowledge stocks and knowledge flows that relate to a practical perspective of wisdom.