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An invisible layer of knowledge is progressively growing with the emergence of situated visualizations and reality-based information retrieval systems. In essence, digital content will overlap with real-world entities, eventually providing insights into the surrounding environment and useful information for the user. The implementation of such a vision may appear close, but many subtle details separate us from its fulfillment. This kind of implementation, as the overlap between rendered virtual annotations and the camera's real-world view, requires different computer vision paradigms for object recognition and tracking which often require high computing power and large-scale datasets of images. Nevertheless, these resources are not always available, and in some specific domains, the lack of an appropriate reference dataset could be disruptive for a considered task. In this particular scenario, we here consider the problem of wine recognition to support an augmented reading of their labels. In fact, images of wine bottle labels may not be available as wineries periodically change their designs, product information regulations may vary, and specific bottles may be rare, making the label recognition process hard or even impossible. In this work, we present augmented wine recognition, an augmented reality system that exploits optical character recognition paradigms to interpret and exploit the text within a wine label, without requiring any reference image. Our experiments show that such a framework can overcome the limitations posed by image retrieval-based systems while exhibiting a comparable performance. [ABSTRACT FROM AUTHOR]

Standardization makes its contributions to many aspects of our lives, although often that contribution is unnoticed. For example, management standards, such as the ISO 9000 family, establish a common ground perspective that enlarges companies' markets and boosts its international reaching, technological development, and innovation while supporting continuous quality improvement in products and services both at a national and international level. Notwithstanding the recognized relevance of some management standards, especially the ones that have an associated certification system to support its knowledge (e.g., ISO 9000 family), little is known about the impact of the standards (e.g., ISO 21500 family) adoption in increasing organizations' performance regarding, for instance, quality, safety, efficiency, or interoperability. This hinders the standards' dissemination and potential use and unnecessarily delays its revision and further development. To help fill this gap, this position paper proposes a research project that includes the development of a model and an observatory focusing on the adoption of management standards. The expected contributions are: 1) at a theoretical level, a new conceptual model for the explanation and assessment of the adoption of management standards and related impacts; 2) at a practical level, a new information system (observatory) which is expected to be a tool for understanding the adoption of standards, as well as for monitoring and publicizing the results obtained from standardization practices. [ABSTRACT FROM AUTHOR]

Information recording and encryption/decryption functions are essential due to the prevalence of counterfeiting activities and information leakage in the current age. However, the development of high‐resolution information recording and multistage information protection systems to achieve high data security levels, such as self‐erasing encrypted data and time‐controlled data handling, remains limited. Herein, inspired by the information‐recording structure of paper, a multiresponsive nanofiber‐reinforced poly(N‐isopropylacrylamide) (PNIPAM) hydrogel (NCPN hydrogel) with improved mechanical properties, solvent‐induced high‐resolution reversible information recording, self‐encryption, and multi‐decryption capabilities, is proposed. Due to the unique hydrophilic and hydrophobic structures of the hydrogel matrix, ethanol and other polar analogs can be applied as special inks to record information by changing the lower critical solution temperature to achieve the repeatable transmittance variation. The recorded information can be erased via water wiping or ethanol volatilization. Additionally, self‐encryption can be achieved and adjusted based on the ethanol volatilization time and concentration difference, and confidential information can be further decrypted in a water environment or under a thermal stimulus. Furthermore, several stable, repeatable, and fast‐response hydrogel‐based information‐recognition systems are designed and investigated. Therefore, the designed hydrogel‐based informational platform provides a universal information‐handling system allowing for the reversible recording of information, with self‐encryption and multidecryption capabilities. [ABSTRACT FROM AUTHOR]

My Turn is software used to manage several Covid-19 mass vaccination campaigns in California. The objective of this article is to describe the use of My Turn at two points of dispensing in California and comment on process improvements to reduce manual tasks of six identified processes of vaccination–registration, scheduling, administration, documentation, follow-up, and digital vaccine record–and paper. We reviewed publicly available documents of My Turn and patients vaccinated at George R. Moscone Convention Center in San Francisco and Oakland Coliseum Community Vaccination Clinic. For publicly available documents of My Turn, we examined videos of My Turn on YouTube, and documentation from EZIZ, the website for the California Vaccines for Children Program. For patients, we examined publicly available vaccination record cards on Instagram and Google. At the George R. Moscone Convention Center, 329,608 vaccines doses were given. At the Oakland Coliseum Community Vaccination Clinic, more than 500,000 vaccine doses were administered. The use of My Turn can be used to reduce manual tasks and paper for mass vaccinating patients against Covid-19. [ABSTRACT FROM AUTHOR]

This document is an editorial note introducing a special issue of the journal Electronics on the topic of "Trends and Applications in Information Systems and Technologies." The note highlights the importance of information technologies in reshaping business models and improving operational efficiency. It also discusses the challenges associated with information systems, such as cybersecurity issues and data-centric decision-making processes. The special issue includes fourteen selected papers covering topics such as the adoption of blockchain technology, digital business solutions, ICT penetration, processing and information extraction in information systems, and innovative applications of information systems. The note concludes by expressing the hope that readers will find the special issue informative and inspiring for further research. [Extracted from the article]

This is an invited commentary on a paper by Sen et al. (forthcoming). I explain how their paper provides a useful reminder of the need to communicate the practical importance of statistical findings more effectively and more often. I also explain how their recommendations address just a small piece of the issue of practical importance. I describe how we must keep the whole issue in mind and I provide examples from my editorial role at MIS Quarterly. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to identify, classify and analyse temporality in information systems development (ISD) literature. Design/methodology/approach: The authors address the temporality and ISD research gap by using a framework – which classifies time into three categories: conceptions of time, mapping activities to time and actors relating to time. The authors conduct a systematic literature review which investigates time in ISD within the Senior Scholars' Basket, Information Technology & People (IT&P), and top two information systems conferences over the past 20 years. The search strategy resulted in 9,850 studies of which 47 were identified as primary papers. Findings: The results reveal that ISD research is ill equipped for contemporary thinking around time. This systematic literature review (SLR) contributes to ISD by finding the following gaps in the literature: (1) clock time is dominant and all other types of time are under-researched; (2) contributions to mapping activities to time is lacking and existing studies focus on single ISD projects rather multiple complex ISD projects; (3) research on actors relating to time is lacking; (4) existing ISD studies which contribute to temporal characteristics are fragmented and lack integration with other categories of time and (5) ISD methodology papers lack contributions to temporal characteristics and fail to acknowledge and contribute to time as a multifaceted interrelated concept. Originality/value: This work has developed the first SLR on temporality in ISD. This study provides a starting point for ISD researchers and ISD practitioners to test commonly held temporal assumptions of ISD researchers and practitioners. [ABSTRACT FROM AUTHOR]

This paper analyzes the usage of vignettes as a narrative form in information systems (IS) research. A review of 48 papers from IS top journals with 119 vignettes exposes the versatile usage of vignettes as a narrative form and shows their usefulness in research communication. The paper conceptualizes vignette usage through a taxonomy and archetypes. To support the future dissemination of this useful narrative technique, it further derives recommendations and guidance for scholars. [ABSTRACT FROM AUTHOR]

Most academic researchers use the academic information system when they want to write a reference, such as a related research for a paper. Specific classification rules are applied based on vast amounts of data and the latest references to classify and search keywords. Meta information is designed for specific classification rules and search results are restructured. The search results can be classified and rearranged to suit academic research paper keywords by applying the restructured classification system and the LDA-based topic modeling technique. To implement this, the ElasticSearch classification method and topic-based LDA model were applied to extract the characteristics of academic papers in this study. Stable topics that could detect topic estimation and keyword search results within the minimum time were extracted to classify the paper search results. In addition, by analyzing the distribution of document weight among topics, the system performance was proven to be excellent. [ABSTRACT FROM AUTHOR]

The article reports on the awarding of the SOFW Journal Best Paper Award 2022. The winners were honored during the SEPAWA® CONGRESS 2022. The first place went to the article "Nano or Non-Nano: The Central Aspect of the Measurement Method," which deals with the measurement of nanomaterials in cosmetic products. The second place was awarded to the article "Optimizing Your Resources for Market Information and Product Development," which provides an online database containing detailed information on household care products. The third place was awarded to the article "A Benchmark-Based Eco-Score for Sunscreen to Communicate Environmental Compatibility to the Consumer," which has developed an information system and logo for assessing the environmental compatibility of sunscreens. [Extracted from the article]

Purpose: Much of recent academic and professional interest in exploring digital transformation and enterprise systems has focused on the technology or the organizations' external forces, leaving internal factors, in particular employees, overlooked. The purpose of this paper is to explore digital literacy of employees as an organizational affordance to capture contextual factors within which digital technologies are situated and are used. Design/methodology/approach: We used the evidence-based practice for information systems approach, and undertook a systematic literature review of 30 papers coupled with brainstorming with 11 professional experts on the neglected topic of digital literacy and its assessment. Findings: This paper draws upon affordance theory, and develops a novel framework for conceptualization of digital literacy of employees as an organizational affordance. We do this by distinguishing digital literacy at the individual level and organizational level, and by assessing digital literacy through Information/Cognitive and Social Practice/Articulation affordances. Research limitations/implications: The current paper contributes to the notion of organizational affordances by examining the effect of interactions between employee-technology through digital literacy of employees in using digital technologies. We offer a novel conceptualization of digital literacy to improve understanding of the role of employee in digital transformation and utilization of enterprise systems. Thus, our definition of digital literacy offers an extension to the recent discussions in the IS literature regarding the actualization of affordances by bringing a lens of employees into the process. Practical implications: This paper operationalizes digital literacy at organizational and individual levels, and offers managers a high-level tool to assess digital literacy of their employees. By doing so, managers can achieve the fit between employees' capabilities and digital technologies that will improve affordance actualization and support their digital transformation initiatives. Originality/value: The study is one of early attempts to apply and extend affordance theory on digital literacy at organizational level by not limiting the concept to the individual level. The proposed framework improves the communication among researchers and between researchers and practitioners. [ABSTRACT FROM AUTHOR]

Featured Application: Generation of a Dynamic Innovation Information System (DIIS) for optimized planning and decision-making thanks to the dynamic evaluation of innovations over their life cycle, applying a methodology for Digital Ecosystems in the Fourth Industrial Revolution and an innovation management model based on the Viable System Model. Innovations are essential for global development and market dynamics. Innovation management is central to organizations for gaining adaptability and dynamic capabilities to ensure their sustainability over time. Right decisions are essential for the implementation of innovations. However, on many occasions, especially in the product development process, decisions are taken based on static analysis, qualitative criteria, questionnaires, and/or quantitative evaluations that are outdated. Moreover, many innovation developments do not consider the existing databases in their information systems of similar innovation projects, especially in the early phases of new innovations when evaluations are mainly driven by area, group, or person. Furthermore, inventions are introduced in different regions, plants, and socio-economic situations, providing different results. In this context, considering that innovations shape our current and future world, including all products and services, as well as how humans, organizations, and machines interact, the significance of the paper is clear. Therefore, it is necessary to develop an innovation management model based on the Viable System Model to cope with any potential future environment based on internal organizational capabilities. For this purpose, the paper designs a Digital Ecosystem for the Fourth Industrial Revolution (DE4.0) based on the Plan-Do-Check-Act methodology applicable to any information system consisting of a digital twin, a simulation model, databases from existing information systems, and quality management techniques. This DE4.0 provides a huge advantage for the applicability and scalability of innovations as it allows one to plan, monitor, assess, and improve. Moreover, based on the conceptual model, a generic project evaluation scheme is developed, providing a platform for innovation project management and control during the whole innovation life cycle. As a result, the research provides a scientific and practical contribution for an integrated management of innovations based on the best information and set of techniques available. Based on this framework, a supply-chain case study is developed. The results show how, depending on the intended goals, the past experiences, the evolution of the innovation, and the innovation scope, indicators can be influenced towards reaching the initial goals and reducing the innovation risks. Finally, a discussion about the potential use and role of the DE4.0 for innovation projects and the related learning process is performed. [ABSTRACT FROM AUTHOR]

This paper summarizes librarian research on information visualization as well as general trends in the broader field, highlighting the most recent trends, important journals, and which subject disciplines are most involved with information visualization. By comparing librarian research to the broader field, the paper identifies opportunities for libraries to improve their information visualization support services. [ABSTRACT FROM AUTHOR]

Hyper-heuristics have arisen as methods that increase the generality of existing solvers. They have proven helpful for dealing with complex problems, particularly those related to combinatorial optimization. Their recent growth in popularity has increased the daily amount of text in the related literature. This information is primarily unstructured, mainly text that traditional computer data systems cannot process. Traditional systematic literature review studies exhibit multiple limitations, including high time consumption, lack of replicability, and subjectivity of the results. For this reason, text mining has become essential for researchers in recent years. Therefore, efficient text mining techniques are needed to extract meaningful information, patterns, and relationships. This study adopts a literature review of 963 journal and conference papers on hyper-heuristic-related works. We first describe the essential text mining techniques, including text preprocessing, word clouds, clustering, and frequent association rule learning in hyper-heuristic publications. With that information, we implement visualization tools to understand the most frequent relations and topics in the hyper-heuristic domain. The main findings highlight the most dominant topics in the literature. We use text mining analysis to find widespread manifestations, representing the significance of the different areas of hyper-heuristics. Furthermore, we apply clustering to provide seven categories showing the associations between the topics related to hyper-heuristic literature. The vast amount of data available that we find opens up a new opportunity for researchers to analyze the status of hyper-heuristics and help create strategic plans regarding the scope of hyper-heuristics. Lastly, we remark that future work will address the limitations of collecting information from multiple data sources and analyze book chapters related to hyper-heuristics. [ABSTRACT FROM AUTHOR]

Particularly, the relational database management systems and the big data systems (e.g., Key-Value stores, Document stores, Graph stores and Graph Computation Systems, Spark, MapReduce/Hadoop, or Data Stream Processing Systems) have evolved with novel additions and extensions. The paper by Harish Kumar Harihara Subramanian et al. on supporting DBMS GPU-based operations with out-of-the-box libraries describes the ongoing research in the database community regarding the use of GPUs for query processing. Data management systems have evolved in terms of functionality, performance characteristics, complexity, and variety during the last 40 years. [Extracted from the article]

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Artificial intelligence (AI) is an important source of competitive advantage as it enables task augmentation and automation. However, while AI can create significant value, it is important to note that AI investments are fraught with risks and uncertainties. Thus, managers are likely to carefully evaluate potential AI investments before committing to investing. However, we know little about how managers' appraisal of AI influences their investment choices. Drawing upon theorization in the areas of business value of AI, agentic information systems (IS) appraisal, and time-situated agency, we extend existing theory in two ways: (1) development of an AI classification (foundational typology) that proposes two dimensions (action autonomy and learning autonomy) for classifying AI by type and level of autonomy; and (2) development of propositions that leverage time-situated agency and the AI classification to explicate how managers' delegation preferences influence their AI investment appraisal. This paper contributes a foundational theoretical platform for furthering AI investment appraisal research. In addition, the paper sets an agenda for future research in this area. [ABSTRACT FROM AUTHOR]

Albeit in different ways, both machine learning and gamification have transfigured the user experience of information systems. Although both are hot research topics, so far, little attention has been paid to how these two technologies converge with each other. This relation is not obvious as while it is feasible to enhance gamification with machine learning, it is also feasible to support machine learning with gamification; moreover, there are applications in which machine learning and gamification are combined yet not directly connected. In this study, we aim to shed light on the use of both machine learning in gamification and gamification in machine learning, as well as the related topics of using gamification in machine learning education and machine learning in gamification research. By performing a systematic literature mapping, we not only identify prior works addressing these respective themes, but also analyze how their popularity evolved in time, investigate the areas of application reported by prior works, used machine learning techniques and software tools, as well as the character of research contribution and the character of evaluation results for works that presented them. [ABSTRACT FROM AUTHOR]

This paper systematically reviews literature with the aim of conceptualizing a change management framework for the effective use of the Examination Administration System (EAS). Information systems (IS) change management factors in the implementation and the post-implementation phases are systematically reviewed to identify 37 reports between 2015 and 2023 and content was analyzed. Postacceptance phase poses many challenges that often result in resistance from the user community thus relinquishing the expected gains. This paper explains change management factors in the postimplementation phase of information systems as they are not adequately addressed in existing literature. The conceptualization of the change management framework draws on the integration of the Unified Theory of Acceptance, Use of Technology and Effective Use Theory and nine change management factors as facilitating conditions. The paper concludes that effective use of EAS is realized through change management factors (i.e., user training, top management support activities, information flow, planning EAS as a change, change shared vision, performance measurement, user involvement and change recognition, user satisfaction and effective communication). This study further adds the indirect mechanisms (i.e., technology use and IS adaptive use) through which the change management factors can impact effective use. The study provides a useful guide to the practitioners and researchers to explain the change management strategies for the effective use of information systems and improve it. This paper also proposes that future studies adapt and/or empirically test conceptual change management apparatus for effective use to ascertain its validity within various contexts. [ABSTRACT FROM AUTHOR]

Augmented reality (AR) technology enables paper maps to dynamically express three-dimensional geographic information, realizing the fusion of virtual and real information. However, in the current mainstream AR development software, the virtual information usually consists of prefabricated components (prefabs), and the content creation for AR maps heavily relies on manual prefabrication. It leads to repetitive and error-prone prefabrication work, which restricts the design of the dynamic, interactive functions of AR maps. To solve this problem, this paper explored the possibility of automatically generating AR map prefabs using object detection models to establish a data conversion interface from paper maps to AR maps. First, we compared and analyzed various object detection models and selected YOLOv8x to recognize map point symbols. Then, we proposed a method to automatically generate AR map prefabs based on the predicted bounding boxes of the object detection model, which could generate prefabs with corresponding categories and positional information. Finally, we developed an AR map prototype system based on Android mobile devices. We designed an interaction method for information queries in the system to verify the effectiveness of the method proposed in this paper. The validation results indicate that our method can be practically applied to the AR map prefabrication process and can quickly generate AR map prefabs with high information accuracy. It alleviated the repetitive workload established through the manual prefabrication method and had specific feasibility and practicality. Moreover, it could provide solid data support for developing dynamic interactive functions of AR maps. [ABSTRACT FROM AUTHOR]

Having a system to process and store information securely is crucial for an e-learning environment in a higher learning institute. Data recorded manually is deemed unsuitable as it may lead to mishandling of documents, poor record of documents movements, and even missing documents. A final year project (FYP) subject for a particular university's course would need a specific management system to alleviate the work processes of supervision and monitor student progress. This system would reduce cost, paperwork, staffing and even simplify the workflow process. Therefore, introducing a student dashboard-based system for the FYP course is proposed in this study. This paper presents a smart system utilizing data analytics and a dashboard that enables the students to self-monitor, track progress and manage important information related to their FYP. The system development followed stepwise Rapid Application Development (RAD) methodology in developing the system. The developed system has been designed, developed, and tested by university students taking FYP courses. A Technology Acceptance Model (TAM) was adopted in the testing phase to examine the system acceptance and user behavior intention in using the proposed system. The results showed a significant effect on a positive implementation in the faculty's course management and monitoring the student's FYP progress. For the dashboardbased system to reach its full potential, it is highly recommended to implement the system in its course management fully. [ABSTRACT FROM AUTHOR]

Objective: The objective of the study is to explore the scientific literature between ultraprocessed foods (UPFs) and cancer using a scientometric mapping. Materials and Methods: A Scopus search was conducted on February 4, 2024, limited to papers published between 2018 and 2023. We found 662 articles, 189 reviews, 68 book chapters, 13 conference papers, and 9 notes. The whole analysis included the evaluation of scholarly output by country/region, the number of scholarly papers produced (scholarly output), the number of views (view count), the field‐weighted citation impact (FWCI). Results: In the analysis conducted for the period 2018–2023, a dataset was examined where the annual growth rate was 5.96%, indicating a sustained expansion of the literature. The average number of citations per paper was 18.56, underlining the impact and relevance of the publications. Sixty‐six single‐authored papers were identified, and international collaborations accounted for 27.23% of the collaborative efforts. The most prominent authors were Inge Huybrechts, Marc J.R. Gunter, and Edward Luciano Giovannucci. In terms of impact and visibility, Harvard University leads with 52 contributions and a field‐weighted impact of 3.39. Conclusions: The literature in the field of UPFs and cancer has experienced a sustained expansion. The scientometric indicators reveal a high activity of recent academic contributions with significant impact. [ABSTRACT FROM AUTHOR]

This paper provides empirical evidence using two studies to explain the primary factors facilitating electronic health record (EHR) systems adoption through the lens of the resource advantage theory. We aim to address the following research questions: What are the main organizational antecedents of EHR implementation? What is the role of monitoring in EHR system implementation? What are the current themes and people's attitudes toward EHR systems? This paper includes two empirical studies. Study 1 presents a research model based on data collected from four different archival datasets. Drawing upon the resource advantage theory, this paper uses archival data from 200 Texas hospitals, thus mitigating potential response bias and enhancing the validity of the findings. Study 2 includes a text analysis of 5154 textual data, sentiment analysis, and topic modeling. Study 1's findings reveal that joint ventures and ownership are the two main enablers of adopting EHR systems in 200 Texas hospitals. Moreover, the results offer a moderating role of monitoring in strengthening the relationship between joint-venture capability and the implementation of EHR systems. Study 2's results indicate a positive attitude toward EHR systems. The U.S. was unique in the sample due to its slower adoption of EHR systems than other developed countries. Physician burnout also emerged as a significant concern in the context of EHR adoption. Topic modeling identified three themes: training, healthcare interoperability, and organizational barriers. In a multimethod design, this paper contributes to prior work by offering two new EHR antecedents: hospital ownership and joint-venture capability. Moreover, this paper suggests that the monitoring mechanism moderates the adoption of EHR systems in Texas hospitals. Moreover, this paper contributes to prior EHR works by performing text analysis of textual data to carry out sentiment analysis and topic modeling. [ABSTRACT FROM AUTHOR]

Accounting has been evolving to follow the latest economic, political, social, and technological developments. Therefore, there is a need for researchers to also include in their research agenda the emerging topics in the accounting area. This exploratory paper selects technological matters in accounting as its research object, proposing a literature review that uses archival research as a method and content analysis as a technique. Using different tools for the assessment of qualitative data, this content analysis provides a summary of those papers, such as their main topics, most frequent words, and cluster analysis. A top journal was used as the source of information, namely The International Journal of Accounting Information Systems, given its scope, which links accounting and technological matters. Data from 2000 to 2022 was selected to provide an evolutive analysis since the beginning of this century, with a particular focus on the latest period. The findings indicate that the recent discussions and trending topics in accounting, including matters such as international regulation, the sustainable perspective in accounting, as well as new methods, channels, and processes for improving the entities' auditing and reporting, have increased their relevance and influence, enriching the debate and future perspectives in combination with the use of new technologies. Therefore, this seems to be a path to follow as an avenue for future research. Notwithstanding, emerging technologies as a research topic seem to be slower or less evident than their apparent development in the accounting area. The findings from this paper are limited to a single journal and, therefore, this limitation must be considered in the context of those conclusions. Notwithstanding, its proposed analysis may contribute to the profession, academia, and the scientific community overall, enabling the identification of the state of the art of literature in the technological area of accounting. [ABSTRACT FROM AUTHOR]

Over the past decades, companies have continually sought out approaches that help them reduce the innovation cycle time due to its importance in their success. Among these approaches are TRIZ-based systematic inventive design processes, such as Inventive Design Methodology (IDM). Nevertheless, the application of these methods in the initial analysis, which requires an exhaustive gathering of information at the start of the innovation project without considering its impact on the final solution, decreases the agility of these types of processes. Consequently, a lean-based method called Inverse Problem Graph (IPG) has been proposed to formulate problems in the initial analysis phase of the inventive design process. However, the manual gathering of essential information to create a network of problems in the IPG method requires time and effort, which impresses the method's capability. This paper integrates an automatic information retrieval approach, using Doc2vec and Cosine Similarity as Artificial Intelligence methods and Scientific Papers, into the IPG process. The integration helps to introduce a new method for the initial analysis phase of inventive design, helping to resolve part of its drawback in collecting essential knowledge from Scientific Data. The capability of the proposal is then tested through an application using a Lattice Structure case study. • This study introduces an automatic information retrieval-based method to formulate a problem situation. • It integrates the doc2vec model and the cosine similarity method into the inventive design process. • The proposal facilitates and accelerates problem formulation in the inventive design. • The proposed method increases the accuracy of problem formulation in the inventive design. [ABSTRACT FROM AUTHOR]

The paper "Charge prediction modeling with interpretation enhancement driven by double-layer criminal system" by Li et al. studies AI methods to predict legal judgments that has become a hot spot in recent years. The 21th International Conference on Web Information Systems Engineering (WISE 2020) was held in Amsterdam, Netherlands, October 20-24, 2020. In order to effectively extract both intra- and inter-session dependencies from not only the session information but also the side information, to further improve the accuracy of next-item recommendations, this paper proposes a novel hypergraph learning (HL) framework. [Extracted from the article]

Artificial intelligence (AI) is becoming increasingly important, especially in the medical field. While AI has been used in medicine for some time, its growth in the last decade is remarkable. Specifically, machine learning (ML) and deep learning (DL) techniques in medicine have been increasingly adopted due to the growing abundance of health-related data, the improved suitability of such techniques for managing large datasets, and more computational power. ML and DL methodologies are fostering the development of new "intelligent" tools and expert systems to process data, to automatize human–machine interactions, and to deliver advanced predictive systems that are changing every aspect of the scientific research, industry, and society. The Italian scientific community was instrumental in advancing this research area. This article aims to conduct a comprehensive investigation of the ML and DL methodologies and applications used in medicine by the Italian research community in the last five years. To this end, we selected all the papers published in the last five years with at least one of the authors affiliated to an Italian institution that in the title, in the abstract, or in the keywords present the terms "machine learning" or "deep learning" and reference a medical area. We focused our research on journal papers under the hypothesis that Italian researchers prefer to present novel but well-established research in scientific journals. We then analyzed the selected papers considering different dimensions, including the medical topic, the type of data, the pre-processing methods, the learning methods, and the evaluation methods. As a final outcome, a comprehensive overview of the Italian research landscape is given, highlighting how the community has increasingly worked on a very heterogeneous range of medical problems. [ABSTRACT FROM AUTHOR]

In recent years, with the continuous expansion of artificial intelligence (AI) application forms and fields, users' acceptance of AI applications has attracted increasing attention from scholars and business practitioners. Although extant studies have extensively explored user acceptance of different AI applications, there is still a lack of understanding of the roles played by different AI applications in human–AI interaction, which may limit the understanding of inconsistent findings about user acceptance of AI. This study addresses this issue by conducting a systematic literature review on AI acceptance research in leading journals of Information Systems and Marketing disciplines from 2020 to 2023. Based on a review of 80 papers, this study made contributions by (i) providing an overview of methodologies and theoretical frameworks utilized in AI acceptance research; (ii) summarizing the key factors, potential mechanisms, and theorization of users' acceptance response to AI service providers and AI task substitutes, respectively; and (iii) proposing opinions on the limitations of extant research and providing guidance for future research. [ABSTRACT FROM AUTHOR]

Objective: To synthesize the best available evidence on the relationship between the social determinants of health and health outcomes among adults during the COVID‐19 pandemic. Introduction: COVID‐19 has created widespread global transmission. Rapid increase in individuals infected with COVID‐19 prompted significant public health responses from governments globally. However, the social and economic impact on communities may leave some individuals more susceptible to the detrimental effects. Methods: A three‐step search strategy was used to find published and unpublished papers. Databases searched included: MEDLINE, CINAHL, EMBASE, and Google Scholar. All identified citations were uploaded into Endnote X9, with duplicates removed. Methodological quality of eligible papers was assessed by two reviewers, with meta‐synthesis conducted in accordance with JBI methodology. Results: Fifteen papers were included. Three synthesized‐conclusions were established (a) Vulnerable populations groups, particularly those from a racial minority and those with low incomes, are more susceptible and have been disproportionately affected by COVID‐19 including mortality; (b) Gender inequalities and family violence have been exacerbated by COVID‐19, leading to diminished wellbeing among women; and (c) COVID‐19 is exacerbating existing social determinants of health through loss of employment/income, disparities in social class leading to lack of access to health care, housing instability, homelessness, and difficulties in physical distancing. Conclusion: Reflection on social and health policies implemented are necessary to ensure that the COVID‐19 pandemic does not exacerbate health inequalities into the future. [ABSTRACT FROM AUTHOR]

This is a qualitative review of the information systems used by public sector organisations in Saudi Arabia. The Google Scholar database was searched to select the papers dealing with IS in other countries and then specifically in Saudi Arabia. The selected papers were discussed under the sections of IS, IT, e-government, and information security in the case of other countries and under the sections of IS, IT, Knowledge management, and e-government in the case of Saudi Arabia. The difference between other countries and Saudi Arabia in the number of papers on each topic was considered to suggest future research topics. Some limitations of this review were also mentioned at the end. [ABSTRACT FROM AUTHOR]

Blockchain, as a decentralized platform and distributed ledger database, will promote the centralized system to form a comprehensive ecosystem. A systematic review of blockchain research on information systems during the five-year period from 2016 to 2020 selected 46 papers from 16 leading journals. This paper introduces the technological characteristics and implementation models, highlighting its research status and development. Moreover, this paper illustrates the future research directions for blockchain. The objective of this paper is to discuss the emerging technology of blockchain in its early development stage and to depict the relevant IS issues that are worthy of further investigation. [ABSTRACT FROM AUTHOR]

The advancement of artificial intelligence technology in recent years has had a significant impact on various industries, including the field of systems engineering. Generative Artificial Intelligence (AI), like OpenAI's ChatGPT, is one such tool that has garnered attention. While this technology offers researchers in systems engineering intriguing possibilities, it also introduces certain risks to the traditional research framework. The aim of this paper is to investigate the advantages and drawbacks associated with embracing generative AI. We conducted a comprehensive literature review utilizing resources like Google Scholar, Web of Science, and the Scopus database, along with professional websites and white papers. The analysis highlights the potential benefits of generative AI in systems engineering research, including data processing, analysis, hypothesis formulation, prediction and forecasting, and collaboration enhancement. However, it also underscores various risks, such as potential data bias, the generation of human-like text, potential loss of analytical capabilities, and difficulties in analyzing output from these AI tools. As emphasized in this paper, numerous concerns still need to be addressed regarding the use of generative AI tools due to their relatively new nature and evolving capabilities. [ABSTRACT FROM AUTHOR]

The object of research is the reliability of information in information-control systems. The work considers a solution to an important scientific and practical problem – increasing the reliability of information in real-time control systems, in particular in positioning systems on road transport. To solve this task, the use of information redundancy, in particular, parallel information redundancy, is proposed. The paper studies the influence of the probability of occurrence of a controlled event, the majority coefficient, as well as the number and quality of information sensors on the reliability of information in an information control system with parallel information redundancy. For these dependences, the corresponding plots were constructed. The paper shows that a change in the quality of information sensors by 20 % can lead to an increase in the reliability of information by more than 0.5. Also, the paper shows that an increase in the majority index by 1 can lead to a change in the reliability of information by more than 0.3. The paper investigates parallel information redundancy systems with different structures and defines formulas for calculating the probabilistic characteristics of their operation. The mathematical modeling was carried out taking into account the probability of occurrence of the controlled event, which made it possible to determine the tendencies to build information-control systems with parallel information redundancy to control events with variable probability of occurrence. The results obtained are based on the theory of probability. The results reported in this work can be used in the construction of an information and control system with a programmatically variable structure to control the occurrence of an event with a variable probability of occurrence, in particular in positioning systems on road transport. [ABSTRACT FROM AUTHOR]

Quantum information mobilizes the description of quantum systems, their states, and their behavior. Since a measurement postulate introduced by von Neumann in 1932, if a quantum system has been prepared in two different mixed states represented by the same density operator ρ , these preparations are said to have led to the same mixture. For more than 50 years, there has been a lack of consensus about this postulate. In a 2011 article, considering variances of spin components, Fratini and Hayrapetyan tried to show that this postulate is unjustified. The aim of the present paper is to discuss major points in this 2011 article and in their reply to a 2012 paper by Bodor and Diosi claiming that their analysis was irrelevant. Facing some ambiguities or inconsistencies in the 2011 paper and in the reply, we first try to guess their aim, establish results useful in this context, and finally discuss the use or misuse of several concepts implied in this debate. [ABSTRACT FROM AUTHOR]

This paper offers a novel perspective on trust in artificial intelligence (AI) systems, focusing on the transfer of user trust in AI creators to trust in AI systems. Using the agentic information systems (IS) framework, we investigate the role of AI alignment and steerability in trust transference. Through four randomized experiments, we probe three key alignment-related attributes of AI systems: creator-based steerability, user-based steerability, and autonomy. Results indicate that creator-based steerability amplifies trust transference from AI creator to AI system, while user-based steerability and autonomy diminish it. Our findings suggest that AI alignment efforts should consider the entity with which the AI goals and values should be aligned and highlight the need for research to theorize from a triadic view encompassing the user, the AI system, and its creator. Given the diversity in individual goals and values, we recommend that developers move beyond the prevailing "one-size-fits-all" alignment strategy. Our findings contribute to trust transference theory by highlighting the boundary conditions under which trust transference breaks down or holds in the emerging human-AI environment. [ABSTRACT FROM AUTHOR]

The article presents the discussion on 21st century being termed as the century of disasters. Topics include blockchain for disaster logistics, wearable technologies for rescue teams and victims, and remote monitoring sensors for intelligence gathering; and Geographic Information System (GIS) for crisis mapping, social media for disaster information dissemination, and extraction of real-time intelligence.

Conceptual modeling is an important part of information systems development and use that involves identifying and representing relevant aspects of reality. Although the past decades have experienced continuous digitalization of services and products that impact business and society, conceptual modeling efforts are still required to support new technologies as they emerge. This paper surveys research on conceptual modeling over the past five decades and shows how its topics and trends continue to evolve to accommodate emerging technologies, while remaining grounded in basic constructs. We survey over 5,300 papers that address conceptual modeling topics from the 1970s to the present, which are collected from 35 multidisciplinary journals and conferences, and use them as the basis from which to analyze the progression of conceptual modeling. The important role that conceptual modeling should play in our evolving digital world is discussed, and future research directions proposed. [ABSTRACT FROM AUTHOR]

Purpose: This paper presents application solutions related to the use of Fourth Industrial Revolution technologies in industry. The aim of the paper is including in a discussion about new trends in the development of information systems supporting monitoring, control and diagnostics of production processes. The objective was realised using the example of continuous production in steelworks. Design/methodology/approach: The aim of the paper was realized in theoretical and practical part of the paper. The empirical part of the was the form of a case study – approach to mathematical model for predicting the enthalpy of foundry ladles. Findings: The conclusion is simply: each industrial branch has to use own transformation path towards Industry 4.0. Practical implications: Prepared approaches - based on analysis of trends in data processing control system in the continues production - can be used to build algorithm of predictive model in its system. Research limitations/implications: The authors are aware of the limitations resulting from the excessive generality of the model, but they ensure that they will continue research on the implementation of Industry 4.0 technology in the metallurgical (metal) industry, with particular emphasis on the continuous course of manufacturing processes. Originality/value: The value of the paper are prepared approaches to mathematical model for predicting the enthalpy of foundry ladles. [ABSTRACT FROM AUTHOR]