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Publications (10 of 46) Show all publications
Alsouda, Y., Pllana, S. & Kurti, A. (2019). IoT-based Urban Noise Identification Using Machine Learning: Performance of SVM, KNN, Bagging, and Random Forest. In: Proceedings of the International Conference on Omni-Layer Intelligent Systems (COINS '19): . Paper presented at International Conference on Omni-Layer Intelligent Systems (COINS '19), Crete, Greece — May 05 - 07, 2019 (pp. 62-67). New York: ACM Publications
Open this publication in new window or tab >>IoT-based Urban Noise Identification Using Machine Learning: Performance of SVM, KNN, Bagging, and Random Forest
2019 (English)In: Proceedings of the International Conference on Omni-Layer Intelligent Systems (COINS '19), New York: ACM Publications, 2019, p. 62-67Conference paper, Published paper (Refereed)
Abstract [en]

Noise is any undesired environmental sound. A sound at the same dB level may be perceived as annoying noise or as pleasant music. Therefore, it is necessary to go beyond the state-of-the-art approaches that measure only the dB level and also identify the type of noise. In this paper, we present a machine learning based method for urban noise identification using an inexpensive IoT unit. We use Mel-frequency cepstral coefficients for audio feature extraction and supervised classification algorithms (that is, support vector machine, k-nearest neighbors, bootstrap aggregation, and random forest) for noise classification. We evaluate our approach experimentally with a data-set of about 3000 sound samples grouped in eight sound classes (such as car horn, jackhammer, or street music). We explore the parameter space of the four algorithms to estimate the optimal parameter values for classification of sound samples in the data-set under study. We achieve a noise classification accuracy in the range 88% - 94%.

Place, publisher, year, edition, pages
New York: ACM Publications, 2019
Keywords
bootstrap aggregation (Bagging), internet of things (IoT), k-nearest neighbors (KNN), mel-frequency cepstral coefficients (MFCC), random forest, smart cities, support vector machine (SVM), urban noise
National Category
Computer Systems
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-81767 (URN)10.1145/3312614.3312631 (DOI)978-1-4503-6640-3 (ISBN)
Conference
International Conference on Omni-Layer Intelligent Systems (COINS '19), Crete, Greece — May 05 - 07, 2019
Funder
Knowledge Foundation, 20150088, 20150259
Available from: 2019-04-09 Created: 2019-04-09 Last updated: 2019-05-20Bibliographically approved
Memeti, S., Pllana, S., Ferati, M., Kurti, A. & Jusufi, I. (2019). IoTutor: How Cognitive Computing Can Be Applied to Internet of Things Education. In: Leon Strous and Vinton G. Cerf (Ed.), : . Paper presented at IFIPIoT 2018 (pp. 1-16). Springer
Open this publication in new window or tab >>IoTutor: How Cognitive Computing Can Be Applied to Internet of Things Education
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2019 (English)Conference paper, Published paper (Refereed)
Abstract [en]

We present IoTutor that is a cognitive computing solution for education of students in the IoT domain. We implement the IoTutor as a platform-independent web-based application that is able to interact with users via text or speech using natural language. We train the IoTutor with selected scientific publications relevant to the IoT education. To investigate users' experience with the IoTutor, we ask a group of students taking an IoT master level course at the Linnaeus University to use the IoTutor for a period of two weeks. We ask students to express their opinions with respect to the attractiveness, perspicuity, efficiency, stimulation, and novelty of the IoTutor. The evaluation results show a trend that students express an overall positive attitude towards the IoTutor with majority of the aspects rated higher than the neutral value.

Place, publisher, year, edition, pages
Springer, 2019
Series
IFIP Advances in Information and Communication Technology, ISSN 1868-4238 ; 548
Keywords
Internet of Things (IoT), education, cognitive computing, IBM Watson
National Category
Computer Systems
Research subject
Computer and Information Sciences Computer Science
Identifiers
urn:nbn:se:lnu:diva-80835 (URN)10.1007/978-3-030-15651-0_18 (DOI)978-3-030-15651-0 (ISBN)978-3-030-15650-3 (ISBN)
Conference
IFIPIoT 2018
Funder
Knowledge Foundation, 20150088, 20150259
Available from: 2019-02-26 Created: 2019-02-26 Last updated: 2019-05-20Bibliographically approved
Alsouda, Y., Pllana, S. & Kurti, A. (2018). A Machine Learning Driven IoT Solution for Noise Classification in Smart Cities. In: Machine Learning Driven Technologies and Architectures for Intelligent Internet of Things (ML-IoT), August 28, 2018, Prague, Czech Republic: . Paper presented at Machine Learning Driven Technologies and Architectures for Intelligent Internet of Things (ML-IoT), August 28, 2018, Prague, Czech Republic (pp. 1-6). Euromicro
Open this publication in new window or tab >>A Machine Learning Driven IoT Solution for Noise Classification in Smart Cities
2018 (English)In: Machine Learning Driven Technologies and Architectures for Intelligent Internet of Things (ML-IoT), August 28, 2018, Prague, Czech Republic, Euromicro , 2018, p. 1-6Conference paper, Published paper (Refereed)
Abstract [en]

We present a machine learning based method for noise classification using a low-power and inexpensive IoT unit. We use Mel-frequency cepstral coefficients for audio feature extraction and supervised classification algorithms (that is, support vector machine and k-nearest neighbors) for noise classification. We evaluate our approach experimentally with a dataset of about 3000 sound samples grouped in eight sound classes (such as, car horn, jackhammer, or street music). We explore the parameter space of support vector machine and k-nearest neighbors algorithms to estimate the optimal parameter values for classification of sound samples in the dataset under study. We achieve a noise classification accuracy in the range 85% -- 100%. Training and testing of our k-nearest neighbors (k = 1) implementation on Raspberry Pi Zero W is less than a second for a dataset with features of more than 3000 sound samples.

Place, publisher, year, edition, pages
Euromicro, 2018
Keywords
urban noise, smart cities, support vector machine (SVM), k-nearest neighbors (KNN), mel-frequency cepstral coefficients (MFCC), internet of things (IoT)
National Category
Computer Systems
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-81672 (URN)
Conference
Machine Learning Driven Technologies and Architectures for Intelligent Internet of Things (ML-IoT), August 28, 2018, Prague, Czech Republic
Available from: 2019-04-04 Created: 2019-04-04 Last updated: 2019-05-20Bibliographically approved
Dalipi, F., Ferati, M. & Kurti, A. (2018). Integrating MOOCs in Regular Higher Education: Challenges and Opportunities from a Scandinavian Perspective. In: Panayiotis Zaphiris and Andri Ioannou (Ed.), Learning and Collaboration Technologies: Design, Development and Technological Innovation. LCT 2018. Paper presented at 5th International Conference on Learning and Collaboration Technologies, LCT 2018 Held as Part of HCI International 2018; Las Vegas; United States; 15-20 July 2018 (pp. 193-204). Springer, 10924
Open this publication in new window or tab >>Integrating MOOCs in Regular Higher Education: Challenges and Opportunities from a Scandinavian Perspective
2018 (English)In: Learning and Collaboration Technologies: Design, Development and Technological Innovation. LCT 2018 / [ed] Panayiotis Zaphiris and Andri Ioannou, Springer, 2018, Vol. 10924, p. 193-204Conference paper, Published paper (Refereed)
Abstract [en]

MOOCs are increasingly being considered by universities as an integral part of their curriculum. Nevertheless, there are several challenges that to some extent slow this process, where the most important one is the accreditation challenges and financing. These challenges are particularly important in the context of universities in Scandinavian countries where education is mostly free. In order to gain more insights on the status of proliferation of MOOCs in Scandinavian universities and understand any specific challenges, we conducted a study by analyzing two sources of data: research publications and university websites. Further on, these data have been analyzed using a framework that differentiates and categorizes MOOCs in terms of accreditation and scalability. As a result of this analysis, we have identified the remaining challenges as well as a number of opportunities regarding the full integration of MOOCs in the educational system of the Scandinavian Higher Education Institutions.

Place, publisher, year, edition, pages
Springer, 2018
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 10924
Keywords
Denmark, Higher education, MOOCs, Norway, Online learning, Opportunities, Scandinavia, Sweden, Artificial intelligence, Computer science, Computers, Accreditation
National Category
Information Systems, Social aspects
Research subject
Computer and Information Sciences Computer Science, Information Systems
Identifiers
urn:nbn:se:lnu:diva-77804 (URN)10.1007/978-3-319-91743-6_15 (DOI)2-s2.0-85050572535 (Scopus ID)9783319917429 (ISBN)
Conference
5th International Conference on Learning and Collaboration Technologies, LCT 2018 Held as Part of HCI International 2018; Las Vegas; United States; 15-20 July 2018
Funder
Knowledge Foundation, 67110033
Available from: 2018-09-14 Created: 2018-09-14 Last updated: 2018-10-04Bibliographically approved
Ahmedi, F., Ahmedi, L., O'Flynn, B., Kurti, A., Tahirsylaj, S., Bytyçi, E., . . . Salihu, A. (2018). InWaterSense: An Intelligent Wireless Sensor Network for Monitoring Surface Water Quality to a River in Kosovo. Paper presented at Hershey, PA, USA. International Journal of Agricultural and Environmental Information Systems, 9(1), 39-61
Open this publication in new window or tab >>InWaterSense: An Intelligent Wireless Sensor Network for Monitoring Surface Water Quality to a River in Kosovo
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2018 (English)In: International Journal of Agricultural and Environmental Information Systems, ISSN 1947-3192, Vol. 9, no 1, p. 39-61Article in journal (Refereed) Published
Abstract [en]

A shift in water monitoring approach from traditional grab sampling to novel wireless sensors is gaining in popularity not only among researchers but also in the market. These latest technologies readily enable numerous advantageous monitoring arrangements like remote, continuous, real-time, and spatially-dense and broad in coverage measurements, and identification of long-term trends of parameters of interest. Thus, a WSN system is implemented in a river in Kosovo as part of the InWaterSense project to monitor its water quality parameters. It is one of the first state of the art technology demonstration systems of its kind in the domain of water monitoring in developing countries like Kosovo. Water quality datasets are transmitted at pre-programmed intervals from sensing stations deployed in the river to the server at university via the GPRS network. Data is then made available through a portal to different target groups (policy-makers, water experts, and citizens). Moreover, the InWaterSense system behaves intelligently like staying in line with water quality regulatory standards.

Place, publisher, year, edition, pages
IGI Global, 2018
National Category
Other Engineering and Technologies not elsewhere specified
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-68718 (URN)10.4018/IJAEIS.2018010103 (DOI)000429506200003 ()
Conference
Hershey, PA, USA
Projects
InWaterSense
Available from: 2017-11-11 Created: 2017-11-11 Last updated: 2019-05-29Bibliographically approved
Chow, J. A., Törnros, M. E., Waltersson, M., Richard, H., Kusoffsky, M., Lundström, C. F. & Kurti, A. (2017). A design study investigating augmented reality and photograph annotation in a digitalized grossing workstation. Journal of Pathology Informatics, 8, Article ID 31.
Open this publication in new window or tab >>A design study investigating augmented reality and photograph annotation in a digitalized grossing workstation
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2017 (English)In: Journal of Pathology Informatics, ISSN 2229-5089, E-ISSN 2153-3539, Vol. 8, article id 31Article in journal (Refereed) Published
Abstract [en]

Context: Within digital pathology, digitalization of the grossing procedure has been relatively underexplored in comparison to digitalization of pathology slides. Aims: Our investigation focuses on the interaction design of an augmented reality gross pathology workstation and refining the interface so that information and visualizations are easily recorded and displayed in a thoughtful view. Settings and Design: The work in this project occurred in two phases: the first phase focused on implementation of an augmented reality grossing workstation prototype while the second phase focused on the implementation of an incremental prototype in parallel with a deeper design study. Subjects and Methods: Our research institute focused on an experimental and “designerly” approach to create a digital gross pathology prototype as opposed to focusing on developing a system for immediate clinical deployment. Statistical Analysis Used: Evaluation has not been limited to user tests and interviews, but rather key insights were uncovered through design methods such as “rapid ethnography” and “conversation with materials”. Results: We developed an augmented reality enhanced digital grossing station prototype to assist pathology technicians in capturing data during examination. The prototype uses a magnetically tracked scalpel to annotate planned cuts and dimensions onto photographs taken of the work surface. This article focuses on the use of qualitative design methods to evaluate and refine the prototype. Our aims were to build on the strengths of the prototype's technology, improve the ergonomics of the digital/physical workstation by considering numerous alternative design directions, and to consider the effects of digitalization on personnel and the pathology diagnostics information flow from a wider perspective. A proposed interface design allows the pathology technician to place images in relation to its orientation, annotate directly on the image, and create linked information. Conclusions: The augmented reality magnetically tracked scalpel reduces tool switching though limitations in today's augmented reality technology fall short of creating an ideal immersive workflow by requiring the use of a monitor. While this technology catches up, we recommend focusing efforts on enabling the easy creation of layered, complex reports, linking, and viewing information across systems. Reflecting upon our results, we argue for digitalization to focus not only on how to record increasing amounts of data but also how these data can be accessed in a more thoughtful way that draws upon the expertise and creativity of pathology professionals using the systems.

Place, publisher, year, edition, pages
Medknow Publications, 2017
Keywords
Augmented reality, design methods, gross pathology, human–computer interaction, interface design, visualization
National Category
Biomedical Laboratory Science/Technology
Research subject
Computer and Information Sciences Computer Science; Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-68016 (URN)10.4103/jpi.jpi_13_17 (DOI)
Funder
VINNOVA
Available from: 2017-09-18 Created: 2017-09-18 Last updated: 2019-05-20Bibliographically approved
Kurti, A. & Dalipi, F. (2017). Bridging the Gap between Academia and Industry: Lessons Learned from a Graduate IT Professional Development Program. In: Gregory T. Papanikos (Ed.), Abstract Book: 2nd Annual International Conference on Engineering Education & Teaching, 5-8 June 2017, Athens, Greece. Paper presented at 2nd Annual International Conference on Engineering Education & Teaching, 5-8 June 2017, Athens (pp. 27-27). Athens
Open this publication in new window or tab >>Bridging the Gap between Academia and Industry: Lessons Learned from a Graduate IT Professional Development Program
2017 (English)In: Abstract Book: 2nd Annual International Conference on Engineering Education & Teaching, 5-8 June 2017, Athens, Greece / [ed] Gregory T. Papanikos, Athens, 2017, p. 27-27Conference paper, Oral presentation with published abstract (Other academic)
Abstract [en]

The rapid advances of technologies, constantly brings new demands for new skills and expertise of the professionals in IT industry. There is a constant need for people that have in-depth understanding and know how to develop the new innovative services using these new technologies. In these settings, the real challenge is how to find the right persons with the right education in an industry where the in-thing yesterday may be out-of-date tomorrow? To add to this challenge, universities are still “increasingly stove-piped in highly specialized disciplinary fields” (Hurlburt et al., 2010) as well as there is a lack of flexibility for the professionals to have their competences developed. All this points out the great challenges that universities are facing for alignment between academic development within degree curricula and the requirements that industry demands for their specific needs (Falcone et al. 2014). In this research effort we report our experiences from an ongoing Graduate Professional Development Program where we address these challenges through a co-creation process with IT industry based on open innovation. Through this model we bring together research expertise, academic experience and experts from industry in a collaborative process for developing courses to suit the current needs of IT professionals. As an outcome of this process, the course content is tailor-made, as well as everything else in connection, such as: bite-size modules, adjustable pace, open and online educational resources, as well as a flipped classroom approach to teaching. As a result, we have developed and provided so far five courses that have been very well accepted by the IT professional. Thus, in this paper we aim to provide some insights on approaches for facilitating continuous competence development plans for IT professionals within regular university educational offer. 

Place, publisher, year, edition, pages
Athens: , 2017
National Category
Computer and Information Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-67486 (URN)978-960-598-128-0 (ISBN)
Conference
2nd Annual International Conference on Engineering Education & Teaching, 5-8 June 2017, Athens
Funder
Knowledge Foundation
Available from: 2017-08-29 Created: 2017-08-29 Last updated: 2019-05-20Bibliographically approved
Dalipi, F., Idrizi, F. & Kurti, A. (2017). Exploring the Impact of Social Learning Networks in M-Learning: a Case Study in a University Environment. In: Zaphiris, Panayiotis; Ioannou, Andri (Ed.), Panayiotis Zaphiris, Andri Ioannou (Ed.), Learning and Collaboration Technologies Novel Learning Ecosystems: 4th International Conference, LCT 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part I. Paper presented at 4th International Conference, LCT 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017 (pp. 189-198). Vancouver: Springer
Open this publication in new window or tab >>Exploring the Impact of Social Learning Networks in M-Learning: a Case Study in a University Environment
2017 (English)In: Learning and Collaboration Technologies Novel Learning Ecosystems: 4th International Conference, LCT 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part I / [ed] Panayiotis Zaphiris, Andri Ioannou, Vancouver: Springer, 2017, p. 189-198Conference paper, Published paper (Refereed)
Abstract [en]

The high penetration of Internet, advances in mobile computing and the rise of smartphone usage has largely enhanced the use of social media in education. Moreover, nowadays social learning network (SLN) platforms have become an important educational technology component in higher education. Despite the fact that SLN are becoming ubiquitous in the higher education, there is relatively not much empirical work done investigating their purposefulness when integrated into the learning activities. This paper aims at exploring the impact of SLN in mobile assisted learning and to provide empirical evidence as to what extent SLN and mobile learning (M-learning) can improve the learning experiences. For this purpose, a quantitative experimental approach is used, and two survey questionnaires were conducted. The data is collected from 120 participants. In this study, we focus our intention on Edmodo and Kahoot platforms, which represent social media based tools that aid and support collaboration, knowledge sharing and group activities among students. Computer science students of the Tetovo University (TU) used these tools throughout one semester. From this study, there is significant evidence that students are very interested to use this SLN in a M-learning setting, indicating that SLN can be one of the promising pedagogical technologies that could contribute effectively to learning process.

Place, publisher, year, edition, pages
Vancouver: Springer, 2017
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 10295
Keywords
M-learning, Social learning networks, Higher education, Edmodo, Kahoot
National Category
Media and Communication Technology
Research subject
Computer and Information Sciences Computer Science
Identifiers
urn:nbn:se:lnu:diva-67455 (URN)10.1007/978-3-319-58509-3_16 (DOI)000434087100016 ()978-3-319-58508-6 (ISBN)978-3-319-58509-3 (ISBN)
Conference
4th International Conference, LCT 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017
Funder
Knowledge Foundation
Available from: 2017-08-28 Created: 2017-08-28 Last updated: 2019-05-20Bibliographically approved
Dalipi, F., Kurti, A., Zdravkova, K. & Ahmedi, L. (2017). Rethinking the conventional learning paradigm towards MOOC based flipped classroom learning. In: 16th International Conference on Information Technology Based Higher Education and Training (ITHET), 10-12 June, 2017, Ohrid, Macedonia: . Paper presented at 16th International Conference on Information Technology Based Higher Education and Training (ITHET), Ohrid, Macedonia, 10-12 July, 2017. IEEE, Article ID 8067791.
Open this publication in new window or tab >>Rethinking the conventional learning paradigm towards MOOC based flipped classroom learning
2017 (English)In: 16th International Conference on Information Technology Based Higher Education and Training (ITHET), 10-12 June, 2017, Ohrid, Macedonia, IEEE, 2017, article id 8067791Conference paper, Published paper (Refereed)
Abstract [en]

The recent proliferation of Massive Open Online Courses (MOOCs) has initiated a plethora of research endeavors revolving around new pedagogical methods in higher education. Integrating MOOCs in blended learning can be beneficial in different ways for both learners and instructors. In this position paper, we aim to provide a brief and comprehensive review about the challenges that higher education institutions in Macedonia and Kosovo face while coping with the new trends of flexible or blended learning. Moreover, after describing some real cases of MOOC based flipped classroom learning, we also provide some recommendations in order to enhance and enrich learning experience by employing innovative pedagogies.

Place, publisher, year, edition, pages
IEEE, 2017
Series
International Conference on Information Technology Based Higher Education and Training, E-ISSN 2380-1603
Keywords
MOOC, blended learning, higher education, open educational resources, flipped classroom
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science
Identifiers
urn:nbn:se:lnu:diva-68411 (URN)10.1109/ITHET.2017.8067791 (DOI)000426982900007 ()978-1-5386-3968-9 (ISBN)
Conference
16th International Conference on Information Technology Based Higher Education and Training (ITHET), Ohrid, Macedonia, 10-12 July, 2017
Projects
Social Media and Web Technologies for Innovation and Growth
Available from: 2017-10-21 Created: 2017-10-21 Last updated: 2019-05-20Bibliographically approved
Bytyçi, E., Ahmedi, L. & Kurti, A. (2016). Association Rule Mining with Context Ontologies: An Application to Mobile Sensing of Water Quality. In: Garoufallou, Emmanouel; Subirats Coll, Imma; Stellato, Armando; Greenberg, Jane (Ed.), Garoufallou, E., Subirats Coll, I., Stellato, A., Greenberg, J (Ed.), Metadata and Semantics Research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Paper presented at 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016 (pp. 67-78). Cham: Springer
Open this publication in new window or tab >>Association Rule Mining with Context Ontologies: An Application to Mobile Sensing of Water Quality
2016 (English)In: Metadata and Semantics Research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings / [ed] Garoufallou, E., Subirats Coll, I., Stellato, A., Greenberg, J, Cham: Springer, 2016, p. 67-78Conference paper, Published paper (Refereed)
Abstract [en]

Internet of Things (IoT) applications by means of wireless sensor networks (WSN) produce large amounts of raw data. These data might formally be defined by following a semantic IoT model that covers data, meta-data, as well as their relations, or might simply be stored in a database without any formal specification. In both cases, using association rules as a data mining technique may result into inferring interesting relations between data and/or metadata. In this paper we argue that the context has not been used extensively for added value to the mining process. Therefore, we propose a different approach when it comes to association rule mining by enriching it with a context-aware ontology. The approach is demonstrated by hand of an application to WSNs for water quality monitoring. Initially, new ontology, its concepts and relationships are introduced to model water quality monitoring through mobile sensors. Consequently, the ontology is populated with quality data generated by sensors, and enriched afterwards with context. Finally, the evaluation results of our approach of including context ontology in the mining process are promising: new association rules have been derived, providing thus new knowledge not inferable when applying association rule mining simply over raw data.

Place, publisher, year, edition, pages
Cham: Springer, 2016
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-58639 (URN)10.1007/978-3-319-49157-8_6 (DOI)000399947700006 ()2-s2.0-85000384218 (Scopus ID)978-3-319-49157-8 (ISBN)978-3-319-49156-1 (ISBN)
Conference
10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016
Available from: 2016-12-05 Created: 2016-12-05 Last updated: 2019-05-20Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-0512-6350

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