73 10 1739 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Enaya, Yaser Ali Jawad Mohammed, Mohammed Bilal, Ghassan Abdulhussein Date A point or period of time associated with an event in the lifecycle of the resource 2020-11-24 Description An account of the resource This study introduces a novel authentication methodology; it is based on pattern recognition of fingers size and pressure when users touch smartphone screen. By analyzing diagrams of these touches and applying data mining for the first time as an authentication technique, this paper presents three new approaches. First, an exact-range evaluation approach has been verified that size is more recognition consistency than pressure. Second, a pattern-range is a new technique reliance on size frequency position. At last, using a size-range has been facilitated the login. The association rules have been modified to work on finger touchscreen data files. To login, 94.1111% of 18 authorized users are succeeded and 98.9% of 20 unauthorized users are failed. Android device and Android studio are used. Size and pressure are normalized to 1; a training set is applied; the password is not considered. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/17239 10.3991/ijim.v14i19.17239 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/17239/8229 Rights Information about rights held in and over the resource Copyright (c) 2020 Yaser Ali Enaya, Yaser Ali Enaya, Mohammed jawad Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 19 (2020); pp. 163-179 1865-7923 Subject The topic of the resource data trace support factor confidence factor training set exact-range size-range pattern-range Title A name given to the resource Password-free Authentication for Smartphone Touchscreen Based on Finger Size Pattern Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Alotaibi, Reem Ali, Ahlam Alharthi, Haya Almehamdi, Renad Date A point or period of time associated with an event in the lifecycle of the resource 2020-11-24 Description An account of the resource Chatbots have gained increasing importance in today research with a lot of available applications. They are flexible and can be applied in many application domains.  In tourism, Chatbots can recommend sights, hotels, activities, or even full travel plans. Usually, users are required to visit plenty of websites and install different Apps into their mobile phones in order to navigate the city and planning for the trip which is inconvenient and time-consuming. To address this issue, this paper proposes “Smart Guidance”, an AI text-based chatbot that is developed as a mobile application. It simulates a chat with users in a natural language, it also provides a two-way interaction and it is a single point of contact for all user communications. We provide a use case in the city of Jeddah, Saudi Arabia. Jeddah is the second largest city in Saudi Arabia and tourists have various choices when it comes to moving around the city. The final evaluation of the chatbot showed that the bot could understand meanings and users’ requests. Moreover, users found that the interaction is effective, and the responses are provided immediately. Users were satisfied and like the idea that they could express their needs in their natural language. Furthermore, users enjoyed the interaction and felt engaged. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/17201 10.3991/ijim.v14i19.17201 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/17201/8211 Rights Information about rights held in and over the resource Copyright (c) 2020 Reem Alotaibi, Ahlam Ali, Haya Alharthi, Renad Almehamdi Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 19 (2020); pp. 18-30 1865-7923 Subject The topic of the resource Tourism Chatbot Natural Language Processing Machine learning Jeddah Title A name given to the resource AI Chatbot for Tourist Recommendations: A Case Study in the City of Jeddah, Saudi Arabia Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Saleh Hussein, Ameer Salah Khairy, Rihab Mohamed Najeeb, Shaima Miqdad Alrikabi, Haider Th.Salim Date A point or period of time associated with an event in the lifecycle of the resource 2021-03-16 Description An account of the resource The global online communication channel made possible with the internet has increased credit card fraud leading to huge loss of monetary fund in their billions annually for consumers and financial institutions. The fraudsters constantly devise new strategy to perpetrate illegal transactions. As such, innovative detection systems in combating fraud are imperative to curb these losses. This paper presents the combination of multiple classifiers through stacking ensemble technique for credit card fraud detection. The fuzzy-rough nearest neighbor (FRNN) and sequential minimal optimization (SMO) are employed as base classifiers. Their combined prediction becomes data input for the meta-classifier, which is logistic regression (LR) resulting in a final predictive outcome for improved detection. Simulation results compared with seven other algorithms affirms that ensemble model can adequately detect credit card fraud with detection rates of 84.90% and 76.30%. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/17173 10.3991/ijim.v15i05.17173 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/17173/8827 Rights Information about rights held in and over the resource Copyright (c) 2021 Haider Th.Salim Alrikabi, Ameer Saleh Hussein, Rihab Salah Khairy Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 05 (2021); pp. 24-42 1865-7923 Subject The topic of the resource Fraud detection Credit card Ensemble technique Stacking Machine learning Title A name given to the resource Credit Card Fraud Detection Using Fuzzy Rough Nearest Neighbor and Sequential Minimal Optimization with Logistic Regression Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Fuada, Syifaul Rabbani, Raihan Fakhri Majid, Nuur Wachid Abdul Prasetiyo, Prasetiyo Muttaqin, Rahmat Adiono, Trio Islam, Shorful Date A point or period of time associated with an event in the lifecycle of the resource 2021-04-09 Description An account of the resource In this short paper, we prove that smartphones connected to Wi-Fi can be detected (scanned) easily with a Raspberry Pi help. According to the observation, the smartphone eventually broadcasts some packets of data containing MAC layers data. The period of broadcasting data depends on the smartphone’s state (active scanning/sleep). Besides MAC layers data, we also detect/capture other parameters, i.e., wireless signature data transmitted by smartphone (RSSI) and Time-stamp. The RSSI value measured in this test has a range from –30 dBm to –80 dBm. The result proves that different smartphones give different RSSI values (each smartphone emits different power strength). The RSSI value has more significant changes in a short-range (in this test result, 1 to 10 meters) and less significant change in a long-distance (above 20 meters). MAC address, time-stamp, and RSSI scanned/captured successfully through Raspberry Pi from the smartphones can be used as a reference for various purposes/applications in future work, such as Wi-Fi scanning/tracking system. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/17169 10.3991/ijim.v15i07.17169 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/17169/9075 Rights Information about rights held in and over the resource Copyright (c) 2021 Syifaul Fuada, Raihan Fakhri Rabbani, Nuur Wachid Abdul Majid Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 07 (2021); pp. 176-184 1865-7923 Subject The topic of the resource MAC layer data Time-stamp RSSI Smartphone Wi-Fi tracking system Title A name given to the resource Your MAC Address Can be Detected Easily When Your Smartphone Connected to the Wi-Fi Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Non-refereed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Mingsiritham, Kemmanat Koraneekij, Prakob Date A point or period of time associated with an event in the lifecycle of the resource 2020-11-24 Description An account of the resource The purpose of this research was to study the using results of OER mobile application to enhance 21st century skills in information media and technology skills for humanities and social sciences learners. The sample included 33 students who studied in an autonomous university in the Humanities and Social Sciences field. Research instruments consisted of self-assessment form before and after studying, behavior observation form, and assignment evaluation form. Data were analyzed by using mean, standard deviation, dependent t-test, and one way repeated measure.The results showed that information, media and technology skills had average scores after studying higher than before studying with statistical significance at the level of .05 (t = 17.382, p = .000). Students had learning behavior with OER mobile application at very high level (M = 4.52, SD = .26). The analysis of one way repeated measure of assignment evaluation in each period (week 2, week 4, week 6) showed statistically significant at the .05 level. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/17105 10.3991/ijim.v14i19.17105 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/17105/8233 Rights Information about rights held in and over the resource Copyright (c) 2020 kemmanat Mingsiritham, Prakob Koraneekij Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 19 (2020); pp. 197-203 1865-7923 Subject The topic of the resource Application Open Smart Classroom Open learning Information Media and Technology skills Title A name given to the resource The Using Results of OER Mobile Application to Enhance 21st Century Skills in Information Media and Technology Skills for Humanities and Social Sciences Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Non-refereed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Wohllebe, Atilla Ross, Florian Podruzsik, Szilárd Date A point or period of time associated with an event in the lifecycle of the resource 2020-11-24 Description An account of the resource Mobile apps have become massively more important in the retail sector in recent years. A central challenge for retailers is the acquisition of new users for their mobile apps. A potentially interesting target group for this can be a company's existing, satisfied customer base, whereby customer satisfaction is often measured by the willingness to recommend the app or the Net Promoter Score. This paper investigates the influence of the willingness to recommend a retailer by consumers on their willingness to install a mobile app from this retailer. The influence of usage habits is also examined. The analysis of a survey of 105 consumers on a total of five retailers can confirm the hypotheses regarding the willingness to recommend a retailer and the Net Promoter Score (NPS) in particular: With the willingness to recommend, the willingness to install a retailer's app also increases. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/17027 10.3991/ijim.v14i19.17027 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/17027/8225 Rights Information about rights held in and over the resource Copyright (c) 2020 Atilla Wohllebe Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 19 (2020); pp. 124-139 1865-7923 Subject The topic of the resource Mobile App Net Promoter Score Smartphone App Likelihood To Recommend Title A name given to the resource Influence of the Net Promoter Score of Retailers on the Willingness of Consumers to Install Their Mobile App Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource AlKhunzain, Abdulmohsin Suliman Khan, Raja Muhammad Ishtiaq Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-26 Description An account of the resource The life of the common to the students have changed due to spread of COVID-19 9 all around the globe. All the educational institutions were also set to be functioned remotely following the global instructions to meet the challenges to combat the COVID-19. The of current inquiry is the explore the male and female learners on the use of mobile phones for Blackboard learn. The Study survey method to collect the data. 68 participants of the medical majors of the CFY formed the sample for the present study. The findings of the study indicate that learners preferred to use M-blackboard. The results also indicated that backboard which is a form of e-learning can be beneficial if it is used with the traditional classroom teaching to get the potential benefits of the software. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/17003 10.3991/ijim.v15i02.17003 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/17003/8633 Rights Information about rights held in and over the resource Copyright (c) 2021 Abdulmohsin Suliman Alkhunzain Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 02 (2021); pp. 4-17 1865-7923 Subject The topic of the resource Blackboard M-learning Perceptions E-learning Title A name given to the resource The Use of M-Learning: A Perspective of Learners’ Perceptions on M-Blackboard Learn Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Gadebe, Moses Lesiba Kogeda, Okuthe Paul Date A point or period of time associated with an event in the lifecycle of the resource 2020-11-10 Description An account of the resource The availability of Smartphones has increased the possibility of self-monitoring to increase physical activity and behavior change to prevent obesity. However self-monitoring on a Smartphtone comes with some challenges such as unavailability of lightweight classification algorithm, personalized dataset to completely capture bodily postures, subject sensitivity, limited storage and computational power. However, most classification algorithms such as Support Vector Machines, C4.5, Naïve Bayes and K Neighbor relies on larger dataset to accurately predict human activities. In this paper, we present top-k of compressed small personalized dataset to reduce computational cost with increased accuracy. We collected top-k personalized dataset from 13 recruited subjects. After benchmarking our collected dataset we found that the dataset is suitable for tree-oriented algorithm, especially the Random Forest, C4.5 and Boosted tree with accuracy and precision of 100% except for KNN, Support Vector and Naïve Bayes. Further, our top-k personalized dataset improves pruning and overfitting of tree-oriented algorithms. Moreover, the linear consistence of static human activities reveals the potential of our top-k dataset to be replicated to multiple-subject to close subject sensitivity challenge. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/16965 10.3991/ijim.v14i18.16965 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/16965/8129 Rights Information about rights held in and over the resource Copyright (c) 2020 Moses Lesiba Gadebe, Okuthe Paul Kogeda Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 18 (2020); pp. 68-86 1865-7923 Subject The topic of the resource top-k personalized dataset gravimeter filtering technique tree oriented Title A name given to the resource Top-K Human Activity Recognition Dataset Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource I. Alghamdi, Mohammed Date A point or period of time associated with an event in the lifecycle of the resource 2020-09-22 Description An account of the resource The research aimed to conduct an extensive study of machine learning and deep learning methods in cybersecurity. To accomplish the objectives, the research carried out a qualitative study based on secondary data collection to review the available studies and literature. The research has examined three machine learning methods and three deep learning methods to study the most popular techniques used in cybersecurity. During the research, the working mechanism of each method was studied along with their strengths and weaknesses. Also, a comparative discussion has been made to examine the most effective method for cybersecurity. Limitations in the current literature were also identified, and future direction is also given to target and develop the weak areas of machine learning and deep learning methods. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/16953 10.3991/ijim.v14i16.16953 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/16953/7883 Rights Information about rights held in and over the resource Copyright (c) 2020 Haider Th.Salim Alrikabi, Mohammed I. Alghamdi Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 16 (2020); pp. 210-224 1865-7923 Subject The topic of the resource Machine learning Deep learning Cybersecurity Applications Title A name given to the resource Survey on Applications of Deep Learning and Machine Learning Techniques for Cyber Security Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Alghazali, Ahmed M. Ageeli, Uthman M. Date A point or period of time associated with an event in the lifecycle of the resource 2020-09-22 Description An account of the resource The ERP is the main source of business data while store mobile inventory management is one of very important modules in ERP that cover a critical role for retail organizations such as Panda retail company. The goal of this study is to show the high correlation between information and effective decision-making process. Descriptive analysis research method was used in this study where theoretical data collected from published papers, in Jeddah city (60) employees of mobile inventory management system users participated the survey and statistical techniques such as frequency tables, Percentages, Average value, standard deviation, etc. This used survey consists of 3 companies namely the effectiveness of information to support decision making, the effectiveness of store mobile inventory management at Panda retail company, the effectiveness of ERP for organizations. The key results of this study clarifies that it’s very important to have as much as possible data and the relationships between data at any point of time to identify problems, analyze them in order to make the most effective decisions and role of ERP in providing such information at any point of time. Recommendations had been provided such as the importunacy of ERP, modern business applications, and technology to improve business outcomes and provide continues learning and development culture for employees to increase their competencies to use these digital tools. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/16943 10.3991/ijim.v14i16.16943 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/16943/7873 Rights Information about rights held in and over the resource Copyright (c) 2020 Ahmed M. Alghazali, Uthman M. Ageeli Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 16 (2020); pp. 133-149 1865-7923 Subject The topic of the resource Enterprise Resource Planning (ERP) Decision-making Mobile Store Title A name given to the resource The Role of ERP Information to Support Decision Making Process: Field Study on Panda Retail Company (Mobile Inventory Management System) Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article