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25 pages, 2987 KiB

Open AccessArticle

Zero Trust VPN (ZT-VPN): A Systematic Literature Review and Cybersecurity Framework for Hybrid and Remote Work

by Syed Muhammad Zohaib, Syed Muhammad Sajjad, Zafar Iqbal, Muhammad Yousaf, Muhammad Haseeb and Zia Muhammad

Information 2024, 15(11), 734; https://doi.org/10.3390/info15110734 - 17 Nov 2024

Viewed by 337

Abstract

Modern organizations have migrated from localized physical offices to work-from-home environments. This surge in remote work culture has exponentially increased the demand for and usage of Virtual Private Networks (VPNs), which permit remote employees to access corporate offices effectively. However, the technology raises [...] Read more.

Modern organizations have migrated from localized physical offices to work-from-home environments. This surge in remote work culture has exponentially increased the demand for and usage of Virtual Private Networks (VPNs), which permit remote employees to access corporate offices effectively. However, the technology raises concerns, including security threats, latency, throughput, and scalability, among others. These newer-generation threats are more complex and frequent, which makes the legacy approach to security ineffective. This research paper gives an overview of contemporary technologies used across enterprises, including the VPNs, Zero Trust Network Access (ZTNA), proxy servers, Secure Shell (SSH) tunnels, the software-defined wide area network (SD-WAN), and Secure Access Service Edge (SASE). This paper also presents a comprehensive cybersecurity framework named Zero Trust VPN (ZT-VPN), which is a VPN solution based on Zero Trust principles. The proposed framework aims to enhance IT security and privacy for modern enterprises in remote work environments and address concerns of latency, throughput, scalability, and security. Finally, this paper demonstrates the effectiveness of the proposed framework in various enterprise scenarios, highlighting its ability to prevent data leaks, manage access permissions, and provide seamless security transitions. The findings underscore the importance of adopting ZT-VPN to fortify cybersecurity frameworks, offering an effective protection tool against contemporary cyber threats. This research serves as a valuable reference for organizations aiming to enhance their security posture in an increasingly hostile threat landscape. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

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13 pages, 3313 KiB

Open AccessArticle

Geospatial Analysis of the Association Between Medicaid Expansion, Minimum Wage Policies, and Alzheimer’s Disease Dementia Prevalence in the United States

by Abolfazl Mollalo, Sara Knox, Jessica Meng, Andreana Benitez, Leslie A. Lenert and Alexander V. Alekseyenko

Information 2024, 15(11), 688; https://doi.org/10.3390/info15110688 - 1 Nov 2024

Viewed by 954

Abstract

Previous studies indicate that increased healthcare access through Medicaid expansion and alleviation of socioeconomic stressors via higher minimum wages improved health outcomes. This study investigates the spatial relationships between the Medicaid expansion, minimum wage policy, and Alzheimer’s Disease (AD) dementia prevalence across the [...] Read more.

Previous studies indicate that increased healthcare access through Medicaid expansion and alleviation of socioeconomic stressors via higher minimum wages improved health outcomes. This study investigates the spatial relationships between the Medicaid expansion, minimum wage policy, and Alzheimer’s Disease (AD) dementia prevalence across the US. We used county-level AD dementia prevalence adjusted for age, sex, race/ethnicity, and education. Social Vulnerability Index (SVI) data, Medicaid expansion status, and state minimum wage law status were incorporated from CDC, Kaiser Family Foundation, and US Department of Labor sources, respectively. We employed the Getis-Ord Gi* statistic to identify hotspots and cold spots of AD dementia prevalence at the county level. We compared these locations with the overall SVI scores using univariate analyses. We also assessed the proportion of hot and cold spots at the state level based on Medicaid expansion and minimum wage status using the logistic regression model. The most vulnerable SVI quartile (Q4) had the highest number of hotspots (n = 311, 64.8%), while the least vulnerable quartile (Q1) had the fewest hotspots (n = 22, 4.6%) (

χ

² = 307.41, p < 0.01). States that adopted Medicaid expansion had a significantly lower proportion of hotspots compared to non-adopting states (p < 0.05), and the non-adopting states had significantly higher odds of having hotspots than adopting states (OR = 2.58, 95% CI: 2.04–3.26, p < 0.001). Conversely, the non-adopting states had significantly lower odds of having cold spots compared to the adopting states (OR = 0.24, 95% CI: 0.19–0.32, p < 0.01). States with minimum wage levels at or below the federal level showed significantly higher odds of having hotspots than states with a minimum wage above the federal level (OR = 1.94, 95% CI: 1.51–2.49, p < 0.01). Our findings suggest significant disparities in AD dementia prevalence related to socioeconomic and policy factors and lay the groundwork for future causal analyses. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

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29 pages, 4128 KiB

Open AccessArticle

A Context-Based Perspective on Frost Analysis in Reuse-Oriented Big Data-System Developments

by Agustina Buccella, Alejandra Cechich, Federico Saurin, Ayelén Montenegro, Andrea Rodríguez and Angel Muñoz

Information 2024, 15(11), 661; https://doi.org/10.3390/info15110661 - 22 Oct 2024

Viewed by 628

Abstract

The large amount of available data, generated every second via sensors, social networks, organizations, and so on, has generated new lines of research that involve novel methods, techniques, resources, and/or technologies. The development of big data systems (BDSs) can be approached from different [...] Read more.

The large amount of available data, generated every second via sensors, social networks, organizations, and so on, has generated new lines of research that involve novel methods, techniques, resources, and/or technologies. The development of big data systems (BDSs) can be approached from different perspectives, all of them useful, depending on the objectives pursued. In particular, in this work, we address BDSs in the area of software engineering, contributing to the generation of novel methodologies and techniques for software reuse. In this article, we propose a methodology to develop reusable BDSs by mirroring activities from software product line engineering. This means that the process of building BDSs is approached by analyzing the variety of domain features and modeling them as a family of related assets. The contextual perspective of the proposal, along with its supporting tool, is introduced through a case study in the agrometeorology domain. The characterization of variables for frost analysis exemplifies the importance of identifying variety, as well as the possibility of reusing previous analyses adjusted to the profile of each case. In addition to showing interesting findings from the case, we also exemplify our concept of context variety, which is a core element in modeling reusable BDSs. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

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27 pages, 5316 KiB

Open AccessArticle

Phishing and the Human Factor: Insights from a Bibliometric Analysis

by Meltem Mutlutürk, Martin Wynn and Bilgin Metin

Information 2024, 15(10), 643; https://doi.org/10.3390/info15100643 - 15 Oct 2024

Viewed by 904

Abstract

Academic research on the human element in phishing attacks is essential for developing effective prevention and detection strategies and guiding policymakers to protect individuals and organizations from cyber threats. This bibliometric study offers a comprehensive overview of international research on phishing and human [...] Read more.

Academic research on the human element in phishing attacks is essential for developing effective prevention and detection strategies and guiding policymakers to protect individuals and organizations from cyber threats. This bibliometric study offers a comprehensive overview of international research on phishing and human factors from 2006 to 2024. Analysing 308 articles from the Web of Science database, a significant increase in publications since 2015 was identified, highlighting the growing importance of this field. The study revealed influential authors such as Vishwanath and Rao, leading journals like Computers & Security, and key contributing institutions including Carnegie Mellon University. The analysis uncovered strong collaborations between institutions and countries, with the USA being the most prolific and collaborative. Emerging research themes focus on psychological factors influencing phishing susceptibility, user-centric security measures, and the integration of technological solutions with human behaviour insights. The findings highlight the need for increased collaboration between academia and non-academic organizations and the exploration of industry-specific challenges. These insights offer valuable guidance for researchers, practitioners, and policymakers to advance their understanding of phishing attacks, human factors, and resource allocation in this critical aspect of digitalisation, which continues to have significant impacts across business and society at large. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

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17 pages, 610 KiB

Open AccessArticle

Gaussian Kernel Approximations Require Only Bit-Shifts

by R. J. Cintra, Paulo Martinez, André Leite, Vítor A. Coutinho, Fábio M. Bayer, Arjuna Madanayake and Diego F. G. Coelho

Information 2024, 15(10), 618; https://doi.org/10.3390/info15100618 - 9 Oct 2024

Viewed by 593

Abstract

An approach to approximate the 2D Gaussian filter for all possible kernel sizes based on the binary optimization technique is introduced. The approximate filter coefficients are designed as negative powers of two, allowing hardware implementation with remarkable savings in the chip area. The [...] Read more.

An approach to approximate the 2D Gaussian filter for all possible kernel sizes based on the binary optimization technique is introduced. The approximate filter coefficients are designed as negative powers of two, allowing hardware implementation with remarkable savings in the chip area. The proposed approximate filters were evaluated and compared with competing methods using both similarity analysis and edge detection applications. The proposed method and the competing works for masks of size

3 \times 3

,

5 \times 5

, and

7 \times 7

were implemented in a Xilinx Artix-7 FPGA. The proposed method showed up to a 60.0% reduction in DSP usage and a 75.0% increase in the maximum operating frequency when compared with state-of-art methods for the

7 \times 7

kernel size case and a 48.8% reduction in the dynamic power normalized by the maximum operating frequency. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

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20 pages, 3431 KiB

Open AccessArticle

An Independent Learning System for Flutter Cross-Platform Mobile Programming with Code Modification Problems

by Safira Adine Kinari, Nobuo Funabiki, Soe Thandar Aung, Khaing Hsu Wai, Mustika Mentari and Pradini Puspitaningayu

Information 2024, 15(10), 614; https://doi.org/10.3390/info15100614 - 7 Oct 2024

Viewed by 1014

Abstract

Nowadays, with the common use of smartphones in daily lives, mobile applications have become popular around the world, which will lead to a rise in Flutter framework. Developed by Google, Flutter with Dart programming provides a cross-platform development environment to create visually [...] Read more.

Nowadays, with the common use of smartphones in daily lives, mobile applications have become popular around the world, which will lead to a rise in Flutter framework. Developed by Google, Flutter with Dart programming provides a cross-platform development environment to create visually appealing and responsive user interfaces across mobile, web, and desktop platforms using a single codebase. However, due to time and staff limitations, the Flutter/Dart programming course is not included in curricula, even in IT departments in universities. Therefore, independent learning environments for students are essential to meet this growing popularity. Previously, we have developed programming learning assistant system (PLAS) as a web-browser-based self-learning platform for novice students. PLAS offers various types of exercise problems designed to cultivate programming skills step-by-step through a lot of code reading and code writing practices. Among them, one particular type is the code modification problem (CMP), which asks to modify the given source code to satisfy the new specifications. CMP is expected to be solved by novices with little effort if they have knowledge of other programming languages. Thus, PLAS with CMP will be an excellent platform for independent learning. In this paper, we present PLAS with CMP for the independent learning of Flutter/Dart programming. To improve the readability of the source code by students, we provided rich comments on grammar or behaviors. Besides, the code can be downloaded so that students can check and run it on an IDE. For evaluations, we generated 38 CMP instances for basic and multimedia/storage topics in Flutter/Dart programming and assigned them to 21 master students at Okayama University, Japan, who have never studied it. The results confirm the validity of the proposal. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

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17 pages, 4134 KiB

Open AccessArticle

Design and Development Model of a Web Accessibility Ecosystem

by Galina Bogdanova, Todor Todorov, Juliana Dochkova-Todorova, Nikolay Noev and Negoslav Sabev

Information 2024, 15(10), 613; https://doi.org/10.3390/info15100613 - 7 Oct 2024

Viewed by 714

Abstract

The article examines issues of web accessibility ecosystems for people with special needs. Methods, models, accessibility standards, and technologies related to the structure, design, and functionality of the web accessibility ecosystem are studied. The stages of developing an accessibility ecosystem are explored. The [...] Read more.

The article examines issues of web accessibility ecosystems for people with special needs. Methods, models, accessibility standards, and technologies related to the structure, design, and functionality of the web accessibility ecosystem are studied. The stages of developing an accessibility ecosystem are explored. The accessibility of the design, functionalities, structure, and content of a particular ecosystem are presented. Several themes for the design of the system with an emphasis on its accessibility for blind users are explored and analyzed. UX/UI design and the ontological model of accessibility, used in the implementation of the model of the ecosystem and its elements, are studied. A web accessibility ecosystem model has been developed, compliant with the Web Content Accessibility Guidelines and based on semantic technologies. Other qualities of this model are easy access to information resources on the topic of accessibility, convenience for users with different needs, and the possibility of expansion and enrichment in the future. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

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19 pages, 5768 KiB

Open AccessArticle

Graph-Based Semi-Supervised Learning with Bipartite Graph for Large-Scale Data and Prediction of Unseen Data

by Mohammad Alemi, Alireza Bosaghzadeh and Fadi Dornaika

Information 2024, 15(10), 591; https://doi.org/10.3390/info15100591 - 27 Sep 2024

Viewed by 579

Abstract

Recently, considerable attention has been directed toward graph-based semi-supervised learning (GSSL) as an effective approach for data labeling. Despite the progress achieved by current methodologies, several limitations persist. Firstly, many studies treat all samples equally in terms of weight and influence, disregarding the [...] Read more.

Recently, considerable attention has been directed toward graph-based semi-supervised learning (GSSL) as an effective approach for data labeling. Despite the progress achieved by current methodologies, several limitations persist. Firstly, many studies treat all samples equally in terms of weight and influence, disregarding the potential increased importance of samples near decision boundaries. Secondly, the detection of outlier-labeled data is crucial, as it can significantly impact model performance. Thirdly, existing models often struggle with predicting labels for unseen test data, restricting their utility in practical applications. Lastly, most graph-based algorithms rely on affinity matrices that capture pairwise similarities across all data points, thus limiting their scalability to large-scale databases. In this paper, we propose a novel GSSL algorithm tailored for large-scale databases, leveraging anchor points to mitigate the challenges posed by large affinity matrices. Additionally, our method enhances the influence of nodes near decision boundaries by assigning different weights based on their importance and using a mapping function from feature space to label space. Leveraging this mapping function enables direct label prediction for test samples without requiring iterative learning processes. Experimental evaluations on two extensive datasets (Norb and Covtype) demonstrate that our approach is scalable and outperforms existing GSSL methods in terms of performance metrics. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

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17 pages, 313 KiB

Open AccessArticle

On the Extended Adjacency Eigenvalues of a Graph

by Alaa Altassan, Hilal A. Ganie and Yilun Shang

Information 2024, 15(10), 586; https://doi.org/10.3390/info15100586 - 26 Sep 2024

Viewed by 535

Abstract

Let

H

be a graph of order n with m edges. Let

d_{i} = d (v_{i})

be the degree of the vertex

v_{i}

. The extended adjacency matrix

A_{e x} (H)

of

H

is an [...] Read more.

Let

H

be a graph of order n with m edges. Let

d_{i} = d (v_{i})

be the degree of the vertex

v_{i}

. The extended adjacency matrix

A_{e x} (H)

of

H

is an

n \times n

matrix defined as

A_{e x} (H) = (b_{i j})

, where

b_{i j} = \frac{1}{2} (\frac{d_{i}}{d_{j}} + \frac{d_{j}}{d_{i}})

, whenever

v_{i}

and

v_{j}

are adjacent and equal to zero otherwise. The largest eigenvalue of

A_{e x} (H)

is called the extended adjacency spectral radius of

H

and the sum of the absolute values of its eigenvalues is called the extended adjacency energy of

H

. In this paper, we obtain some sharp upper and lower bounds for the extended adjacency spectral radius in terms of different graph parameters and characterize the extremal graphs attaining these bounds. We also obtain some new bounds for the extended adjacency energy of a graph and characterize the extremal graphs attaining these bounds. In both cases, we show our bounds are better than some already known bounds in the literature. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

23 pages, 1584 KiB

Open AccessArticle

Real-Time Identification and Nonlinear Control of a Permanent-Magnet Synchronous Motor Based on a Physics-Informed Neural Network and Exact Feedback Linearization

by Sergio Velarde-Gomez and Eduardo Giraldo

Information 2024, 15(9), 577; https://doi.org/10.3390/info15090577 - 19 Sep 2024

Viewed by 679

Abstract

This work proposes a novel method for the real-time identification and nonlinear control of a permanent-magnet synchronous motor (PMSM) based on a Physics-Informed Neural Network (PINN) and the exact feedback linearization approach. The proposed approach is presented in a direct-quadrature framework, where the [...] Read more.

This work proposes a novel method for the real-time identification and nonlinear control of a permanent-magnet synchronous motor (PMSM) based on a Physics-Informed Neural Network (PINN) and the exact feedback linearization approach. The proposed approach is presented in a direct-quadrature framework, where the quadrature current and the rotational speed are selected as outputs and the direct and quadrature voltages are selected as inputs. A nonlinear difference equation is selected to describe the physical dynamics of the PMSM, and a PINN is designed based on the aforementioned structure. A simplified training scheme is designed for the PINN based on a least-squares structure to facilitate online training in real time. A nonlinear controller based on exact feedback linearization is designed by considering the nonlinear model of the system identified based on the PINN. Therefore, the proposed approach involves identification and control in real time, where the PINN is trained online. In order to track the reference for the rotational speed, a nonlinear controller with integral action based on exact feedback linearization is designed based on a linear quadratic regulator. As a result, the proposed approach can be used to identify the system to be controlled in real time, and it is able to track any small change in the real model; in addition, it is robust to both external and internal disturbances, such as variations in torque load and resistance. The proposed approach is evaluated through simulation and using a real PMSM, and the results of reference tracking are evaluated under disturbances. The identification performance is evaluated by using a Taylor diagram under closed-loop and open-loop structures, where ARX and NARX structures are used for comparison. It is thereby verified that this novel proposed control approach involving a PINN-based model can adequately track the dynamics of a PMSM system, where the performance of the proposed nonlinear control is maintained even when using the identified model based on the PINN. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

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21 pages, 885 KiB

Open AccessArticle

Knowledge Sharing and Organizational Commitment: Psychological Capital as a Mediator and Self-Actualization as Moderator

by Cynthia Sheeba Cathrin Rajakumar, Syed Aktharsha Usman, Mary Pearly Sumathi Soosai Micheal and Satyanarayana Parayitam

Information 2024, 15(8), 459; https://doi.org/10.3390/info15080459 - 2 Aug 2024

Viewed by 1454

Abstract

This study aims to investigate the effect of knowledge sharing on organizational commitment. A conceptual model shows hypothesized relationships between knowledge sharing, psychological capital, and organizational commitment. Further, the roles of self-actualization and gender as moderators have been explored. The model is tested [...] Read more.

This study aims to investigate the effect of knowledge sharing on organizational commitment. A conceptual model shows hypothesized relationships between knowledge sharing, psychological capital, and organizational commitment. Further, the roles of self-actualization and gender as moderators have been explored. The model is tested with data from faculty members from higher educational institutions in southern India. Using a structured survey instrument, data were collected from 368 faculty members and analyzed after testing the instrument’s psychometric properties using LISREL9 software for structural equation modeling. PROCESS macros were used to test hypotheses. The results reveal that (i) knowledge sharing significantly and positively impacts psychological capital and organizational commitment, and (ii) psychological capital mediates the relationship between knowledge sharing and organizational commitment. The results strongly support self-actualization as moderating the relationship between knowledge sharing and psychological capital. Further, gender as a moderator showed that the relationship between knowledge sharing and organizational commitment was stronger for female faculty compared to male faculty members. The theoretical contribution and practical implications are discussed. Keywords: knowledge sharing, psychological capital, organizational commitment, self-actualization, gender, higher educational institutions, India. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

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15 pages, 1422 KiB

Open AccessArticle

Integrating Change Management with a Knowledge Management Framework: A Methodological Proposal

by Bernal Picado Argüello and Vicente González-Prida

Information 2024, 15(7), 406; https://doi.org/10.3390/info15070406 - 13 Jul 2024

Viewed by 2075

Abstract

This study proposes the integration of change management with a knowledge management framework to address knowledge retention and successful change management in the context of Industry 5.0. Using the ADKAR model, it is suggested to implement strategies for training and user acceptance testing. [...] Read more.

This study proposes the integration of change management with a knowledge management framework to address knowledge retention and successful change management in the context of Industry 5.0. Using the ADKAR model, it is suggested to implement strategies for training and user acceptance testing. The research highlights the importance of applying the human capital life cycle in knowledge and change management, demonstrating the effectiveness of this approach in adapting to Industry 5.0. The methodology includes a review of the state of the art in intangible asset management, change management models, and the integration of change and knowledge management. In addition, a case study is presented in a food production company that validates the effectiveness of the ADKAR model in implementing digital technologies, improving process efficiency and increasing employee acceptance of new technologies. The results show a significant improvement in process efficiency and a reduction in resistance to change. The originality of the study lies in the combination of the ADKAR model with intangible asset and knowledge management, providing a holistic solution for change management in the Industry 5.0 era. Future implications suggest the need to explore the applicability of the ADKAR model in different industries and cultures, as well as its long-term effects on organisational sustainability and innovation. This comprehensive approach can serve as a guide for other organisations seeking to implement successful digital transformations. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

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16 pages, 2490 KiB

Open AccessArticle

Constructing Semantic Summaries Using Embeddings

by Georgia Eirini Trouli, Nikos Papadakis and Haridimos Kondylakis

Information 2024, 15(4), 238; https://doi.org/10.3390/info15040238 - 20 Apr 2024

Cited by 1 | Viewed by 1365

Abstract

The increase in the size and complexity of large knowledge graphs now available online has resulted in the emergence of many approaches focusing on enabling the quick exploration of the content of those data sources. Structural non-quotient semantic summaries have been proposed in [...] Read more.

The increase in the size and complexity of large knowledge graphs now available online has resulted in the emergence of many approaches focusing on enabling the quick exploration of the content of those data sources. Structural non-quotient semantic summaries have been proposed in this direction that involve first selecting the most important nodes and then linking them, trying to extract the most useful subgraph out of the original graph. However, the current state of the art systems use costly centrality measures for identifying the most important nodes, whereas even costlier procedures have been devised for linking the selected nodes. In this paper, we address both those deficiencies by first exploiting embeddings for node selection, and then by meticulously selecting approximate algorithms for node linking. Experiments performed over two real-world big KGs demonstrate that the summaries constructed using our method enjoy better quality. Specifically, the coverage scores obtained were 0.8, 0.81, and 0.81 for DBpedia v3.9 and 0.94 for Wikidata dump 2018, across 20%, 25%, and 30% summary sizes, respectively. Additionally, our method can compute orders of magnitude faster than the state of the art. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

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Review

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22 pages, 1032 KiB

Open AccessReview

Revisioning Healthcare Interoperability System for ABI Architectures: Introspection and Improvements

by João Guedes, Júlio Duarte, Tiago Guimarães and Manuel Filipe Santos

Information 2024, 15(12), 745; https://doi.org/10.3390/info15120745 - 21 Nov 2024

Viewed by 170

Abstract

The integration of systems for Adaptive Business Intelligence (ABI) in the healthcare industry has the potential to revolutionize and reform the way organizations approach data analysis and decision-making. By providing real-time actionable insights and enabling organizations to continuously adapt and evolve, ABI has [...] Read more.

The integration of systems for Adaptive Business Intelligence (ABI) in the healthcare industry has the potential to revolutionize and reform the way organizations approach data analysis and decision-making. By providing real-time actionable insights and enabling organizations to continuously adapt and evolve, ABI has the potential to drive better outcomes, reduce costs, and improve the overall quality of patient care. The ABI Interoperability System was designed to facilitate the usage and integration of ABI systems in healthcare environments through interoperability resources like Health Level 7 (HL7) or Fast Healthcare Interoperability Resources (FHIR). The present article briefly describes both versions of this software, learning about their differences and improvements, and how they affect the solution. The changes introduced in the new version of the system will tackle code quality with automated tests, development workflow, and developer experience, with the introduction of Continuous Integration and Delivery pipelines in the development workflow, new support for the FHIR pattern, and address a few security concerns about the architecture. The second revision of the system features a more refined, modern, and secure architecture and has proven to be more performant and efficient than its predecessor. As it stands, the Interoperability System poses a significant step forward toward interoperability and ease of integration in the healthcare ecosystem. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

17 pages, 1444 KiB

Open AccessReview

Governing with Intelligence: The Impact of Artificial Intelligence on Policy Development

by Muhammad Asfand Yar, Mahani Hamdan, Muhammad Anshari, Norma Latif Fitriyani and Muhammad Syafrudin

Information 2024, 15(9), 556; https://doi.org/10.3390/info15090556 - 10 Sep 2024

Viewed by 2591

Abstract

As the field of artificial intelligence (AI) continues to evolve, its potential applications in various domains, including public policy development, have garnered significant interest. This research aims to investigate the role of AI in shaping public policies through a qualitative examination of secondary [...] Read more.

As the field of artificial intelligence (AI) continues to evolve, its potential applications in various domains, including public policy development, have garnered significant interest. This research aims to investigate the role of AI in shaping public policies through a qualitative examination of secondary data and an extensive bibliographic review. By analyzing the existing literature, government reports, and relevant case studies, this study seeks to uncover the opportunities, challenges, and ethical considerations associated with leveraging AI in the formulation and implementation of public policies. This research will delve into the potential benefits of AI-driven policy analysis, such as enhanced decision-making processes, data-driven insights, and improved policy outcomes. Additionally, it will explore the risks and concerns surrounding AI’s influence on policy, including potential biases, privacy implications, and the need for transparency and accountability. The findings of this study will contribute to the ongoing discourse on the responsible and effective integration of AI in public policy development, fostering informed decision-making and promoting the ethical use of this transformative technology. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

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20 pages, 1283 KiB

Open AccessReview

Business Model Evolution in the Age of NFTs and the Metaverse

by Mitra Madanchian and Hamed Taherdoost

Information 2024, 15(7), 378; https://doi.org/10.3390/info15070378 - 28 Jun 2024

Viewed by 1417

Abstract

The dynamic progression of technology has induced a profound metamorphosis within the realm of commerce, ushering in novel prospects and trials for enterprises spanning diverse sectors. In contemporary times, the rise in non-fungible tokens (NFTs) and the conception of the Metaverse have ensnared [...] Read more.

The dynamic progression of technology has induced a profound metamorphosis within the realm of commerce, ushering in novel prospects and trials for enterprises spanning diverse sectors. In contemporary times, the rise in non-fungible tokens (NFTs) and the conception of the Metaverse have ensnared the focus of corporate entities and visionary proprietors alike. This article explores the transformation of business frameworks during the era of NFTs and the Metaverse. It delves into traditional paradigms, clarifies the unique characteristics of NFTs, and examines their potential impacts on commerce. This article investigates the convergence of virtual reality (VR), augmented reality (AR), and blockchain technology within the Metaverse. To investigate these transformations, this study undertakes a comprehensive literature evaluation. The findings highlight how NFTs and the Metaverse have introduced new avenues for generating revenue and creating value. These advancements are achieved through the utilization of smart contracts and adaptable strategies that cater to evolving consumer behaviors. This article also addresses significant challenges in this landscape and provides a forward-looking perspective on the anticipated trajectory. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

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23 pages, 486 KiB

Open AccessReview

Machine Learning for Smart Irrigation in Agriculture: How Far along Are We?

by Marco Del-Coco, Marco Leo and Pierluigi Carcagnì

Information 2024, 15(6), 306; https://doi.org/10.3390/info15060306 - 24 May 2024

Cited by 1 | Viewed by 3838

Abstract

The management of water resources is becoming increasingly important in several contexts, including agriculture. Recently, innovative agricultural practices, advanced sensors, and Internet of Things (IoT) devices have made it possible to improve the efficiency of water use. However, it is the application of [...] Read more.

The management of water resources is becoming increasingly important in several contexts, including agriculture. Recently, innovative agricultural practices, advanced sensors, and Internet of Things (IoT) devices have made it possible to improve the efficiency of water use. However, it is the application of control strategies based on advanced machine learning techniques that enables the adoption of smart irrigation scheduling and the immediate economic, social, and environmental benefits. This challenging research area has attracted the attention of many researchers worldwide, who have proposed several technological and methodological solutions. Unfortunately, the results of these scientific efforts have not yet been categorized in a thematic survey, making it difficult to understand how far we are from optimal water management based on machine learning. This paper fills this gap by focusing on smart irrigation systems with an emphasis on machine learning. More specifically, the generic structure of a smart agriculture system is presented, and existing machine learning strategies and available datasets are discussed. Furthermore, several open issues are identified, especially in the processing of long-term data, also due to the lack of corresponding annotated datasets. Finally, some interesting future research directions to be pursued in order to build scalable, domain-independent approaches are proposed. Full article

(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

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