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  • 1.
    Ahmed, Salah Uddin
    et al.
    University of South-Eastern Norway, Norway.
    Dalipi, Fisnik
    University of South-Eastern Norway, Norway.
    Ferati, Mexhid
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för informatik (IK).
    Plugin: a Crowdsourcing Mobile App for Easy Discovery of Public Charging Outlets2019Inngår i: HCI International 2019: Posters. HCII 2019 / [ed] Stephanidis C., Springer, 2019, Vol. 1034, s. 323-329Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Nowadays, the growth of mobile apps is so fast and viral; they have the potential of transforming our everyday lives by creating huge opportunities to individuals and businesses. This translates into a growing demand for developing such apps, which need to be easy to learn and use. In this paper, we conduct an evaluation of an android mobile app, which we designed and developed to find and register power outlets in public spaces. Our evaluation of the prototype consisted of two stages. First, we provided the users with two tasks, with an additional option to indicate their perception of how easy it was to complete these tasks. Second, upon completing both tasks and offering their comments, participants were asked to take the SUS (System Usability Scores) questionnaire. The results of the evaluation indicate that the app usability and learnability is acceptable despite being a prototype. The findings and participants’ comments give us a direction on how this app can be improved in the future.

  • 2.
    Dalipi, Fisnik
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM). University of South-Eastern Norway, Norway.
    Ferati, Mexhid
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för informatik (IK).
    Kurti, Arianit
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM). RISE - Research Institutes of Sweden.
    Integrating MOOCs in Regular Higher Education: Challenges and Opportunities from a Scandinavian Perspective2018Inngår i: Learning and Collaboration Technologies: Design, Development and Technological Innovation. LCT 2018 / [ed] Panayiotis Zaphiris and Andri Ioannou, Springer, 2018, Vol. 10924, s. 193-204Konferansepaper (Fagfellevurdert)
    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.

  • 3.
    Dalipi, Fisnik
    et al.
    Norwegian University of Science and Technology (NTNU), Norway.
    Ferati, Mexhid
    Oslo and Akershus University College of Applied Sciences (HiOA), Norway.
    Yayilgan, Sule Yildirim
    Norwegian University of Science and Technology (NTNU), Norway.
    User Interface Evaluation of a Ski Injuries Management System2017Inngår i: Advances in Human Factors in Sports and Outdoor Recreation, Orlando, USA: Springer, 2017, s. 213-222Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Although many technological devices and solutions to enhance the skiing experience are now available for skiers, skiing sometimes could turn to be potentially dangerous. The speed of movement, environment unpredictability, and variable weather conditions, among others, can contribute to some of the most common skiing injuries that skiers incur. In this paper, we conduct an interface prototype evaluation of a ski injury registration system architecture that is already developed. This system will improve the communication from the ski resort to the medical center, in case an injury has occurred. The results of the interface evaluation indicate that the ski patrollers showed very positive attitude and experience with this prototype. Furthermore, the post-task and SUS (System Usability Scale) question results showed very high score for all participants, indicating that locating the body parts and the right injury was very easy using the interface.

  • 4.
    Dalipi, Fisnik
    et al.
    State University of Tetova, Makedonia.
    Idrizi, Florim
    State University of Tetova, Makedonia.
    Kamberi, Lazim
    State University of Tetova, Makedonia.
    Determinants of e-business and ICT adoption among SMEs in Macedonia: An application of TOE Framework2011Inngår i: International Symposium on Computing in Informatics and Mathematics; 1st International Symposium on Computing in Informatics and Mathematics, International Symposium on Computing in Informatics and Mathematics , 2011, s. 111-124Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Research has demonstrated that firms using e-business culminate with considerable returns through efficiency improvement, inventory reduction, sales increase,customer relationship enhancement, new market penetration, and ultimatelyfinancial returns. However, there is little systematic research in terms of e-businessadoption patterns in firms using TOE (Technology-Organization-Environment)framework. This paper illustrates the potential of adoption and use of ICT and ebusinessapplications in small and medium sized enterprises (SMEs) in Macedonia.In the paper we present preliminary results of a survey of around 60 SMEs. In thisstudy we explore several factors enabling or impeding the successful adoption anduse of e-business and ICT by Macedonian SMEs. Based on technologyenvironment-organization (TOE) theory, three aspects influence e-business adoption: technological context (we explore technology integration among firms,more specifically the type of ICT adoption and applications), organizational context(we try to discover the motivations to invest in ICT, the benefits and barriers of ICTand e-business in particular) and environmental context (here we investigate trusted sources of IT advice, challenges of implementations and competitive pressure). Wefind that SMEs are generally satisfied with their investment in ICT but they are concerned about the cost of such investments and are uncertain about the business benefits, failing to recognize ICT's strategic potential to increase business flexibility, to increase productivity and to support globalization. Besides the concern about the ICT related cost, other major obstacles in adopting ICT were lackof internal ICT capabilities and lack of information about selecting, implementing and evaluating suitable ICT solutions. Our findings have important implications for policy aimed at ICT adoption and use by SMEs and will provide a foundation forfuture research by helping policy makers to understand, assist and support the SME sector.

  • 5.
    Dalipi, Fisnik
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV). Tetovo University, Macedonia.
    Idrizi, Florim
    Tetovo University, Macedonia.
    Kurti, Arianit
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV). RISE Interactive, Norrköping.
    Exploring the Impact of Social Learning Networks in M-Learning: a Case Study in a University Environment2017Inngår i: 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, s. 189-198Konferansepaper (Fagfellevurdert)
    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.

  • 6.
    Dalipi, Fisnik
    et al.
    Tetovo State University, Macedonia.
    Idrizi, Florim
    Tetovo State University, Macedonia.
    Rufati, Eip
    Tetovo State University, Macedonia.
    Asani, Florin
    Tetovo State University, Macedonia.
    On Integration of Ontologies into E-Learning Systems2014Inngår i: 2014 Sixth International Conference on Computational Intelligence, Communication Systems and Networks (CICSyN), IEEE, 2014, s. 149-152Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Ontologies represent an immense opportunity and are bringing great advantages to e-learning systems. Their implementation is seen as a better solution for organizing and visualizing didactic knowledge, and for this knowledge to be shared and reused by different educational applications. This paper aims at proposing a model which is focused on integrating ontological principles with e-learning standards. We developed a prototype model that is integrated with an ontology which gives a semantic representation of learning contents by adding semantic notations to each learning resource. The ontology is used for identifying the structure of learning module and defining the needed vocabulary for the student to conceptualize the learning modules. Another special ontology is introduced for learning materials, which is located at the systems metadata. Here, we included also the system access options, results registering and the communications.

  • 7.
    Dalipi, Fisnik
    et al.
    Norwegian University of Science and Technology (NTNU), Norway.
    Imran, Ali Shariq
    University of Science and Technology (NTNU), Norway.
    Idrizi, Florim
    Tetovo University, Macedonia.
    Aliu, Hesat
    Tetovo University, Macedonia.
    An Analysis of Learner Experience with MOOCs in Mobile and Desktop Learning Environment2017Inngår i: Learning and Collaboration Technologies. LCT 2016, Orlando, USA: Springer, 2017, s. 393-402Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Massive Open Online Courses (MOOCs) are now the most recent topic within the field of e-learning. They have the potential to influence the higher education environments significantly worldwide by creating a completely new and large market of educational resources by overpassing the traditional universities market share due to their physical limitations. However, due to the many differences between mobile devices and desktop environments, the introduction of mobile technology in MOOC environment is challenging. Hence, the main objective of this paper is to study and compare the learner’s experience in different learning environments by using mobile devices and PCs while performing given tasks related to MOOCs. To achieve this goal, we conduct a subjective experiment with various MOOCs related tasks to be performed in mobile and desktop learning environment. The results of the findings show that the difficulties learners have experienced in the mobile environment are more expressed. Moreover, their satisfactory level is much higher in the desktop environment.

  • 8.
    Dalipi, Fisnik
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV). Univ Coll Southeast Norway, Norway.
    Imran, Ali Shariq
    Norwegian Univ Sci & Technol NTNU, Norway.
    Kastrati, Zenun
    Norwegian Univ Sci & Technol NTNU, Norway.
    MOOC Dropout Prediction Using Machine Learning Techniques: Review and Research Challenges2018Inngår i: Proceedings of 2018 IEEE Global Engineering Education Conference (EDUCON) - Emerging Trends and Challenges of Engineering Education, IEEE, 2018, s. 1007-1014Konferansepaper (Fagfellevurdert)
    Abstract [en]

    MOOC represents an ultimate way to deliver educational content in higher education settings by providing high-quality educational material to the students throughout the world. Considering the differences between traditional learning paradigm and MOOCs, a new research agenda focusing on predicting and explaining dropout of students and low completion rates in MOOCs has emerged. However, due to different problem specifications and evaluation metrics, performing a comparative analysis of state-of-the-art machine learning architectures is a challenging task. In this paper, we provide an overview of the MOOC student dropout prediction phenomenon where machine learning techniques have been utilized. Furthermore, we highlight some solutions being used to tackle with dropout problem, provide an analysis about the challenges of prediction models, and propose some valuable insights and recommendations that might lead to developing useful and effective machine learning solutions to solve the MOOC dropout problem.

  • 9.
    Dalipi, Fisnik
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV).
    Kurti, Arianit
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV). RISE Interactive Institute.
    Zdravkova, Katerina
    Ss. Cyril and Methodius University, Macedonia.
    Ahmedi, Lule
    University of Prishtina, Serbia.
    Rethinking the conventional learning paradigm towards MOOC based flipped classroom learning2017Inngår i: 16th International Conference on Information Technology Based Higher Education and Training (ITHET), 10-12 June, 2017, Ohrid, Macedonia, IEEE, 2017, artikkel-id 8067791Konferansepaper (Fagfellevurdert)
    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.

  • 10.
    Dalipi, Fisnik
    et al.
    Gjovik University College, Norway.
    Mendoza, Diana Marina Armijo
    Gjovik University College, Norway.
    Imran, Ali Shariq
    Gjovik University College, Norway.
    Yayilgan, Sule Yilidrim
    Gjovik University College, Norway.
    An intelligent model for predicting the occurrence of skiing injuries2015Inngår i: 2015 5th National Symposium on Information Technology: Towards New Smart World (NSITNSW),, IEEE, 2015, s. 1-6Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Artificial neural networks offer a unique way to model very complex and innovative systems that can be very effective in anticipating various accident severities. In this article, we propose a neural-network-based model, able to predict the number of severe injuries caused while skiing. The proposed system is intended for use by ski patrol and medical personnel to better prepare themselves in advance for treating ski-injured persons. The ski patrol and any other medical personnel will be able to know the statistics, type and severity of the injuries occurred, and most importantly, will be benefiting from having predictions for each day. Considering that, the number of injured people in a particular place each day was estimated, the results are very promising suggesting that such a system would prove beneficial in accurately predicting skiing injuries.

  • 11.
    Dalipi, Fisnik
    et al.
    Tetovo State University, Makedonien.
    Ninka, Ilia
    Tirana University, Albanien.
    Shej, Ajri
    Tetovo State University, Makedonien.
    Applying semantically adapted vector space model to enhance information retrieval2012Inngår i: ICT Innovations 2012 Web Proceedings: Poster Session / [ed] S. Markovski, M. Gusev, Ohrid: ICT ACT , 2012, s. 573-575Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Abstract. While most enterprise data is unstructured and file based, the need for access to structured data is increasing. In order to reduce the cost for finding information and achieve relevant results there is a need to build a very complex query which indeed is a serious challenge. Data volumes are growing at 60% annually and up to 80% of this data in any organization can be unstructured. In this paper we focus on describing the evolution of some modern ontology-based information retrieval systems. Further, we will provide a brief overview of the key advances in the field of semantic information retrieval from heterogeneous information sources, and a description of where the state-of-the-art is at in the field. Finally, we present and propose a novel use of semantic retrieval model based on the vector space model for the exploitation of KB (Knowledge Base) to enhance and support searching over robust and heterogeneous environments.

  • 12.
    Dalipi, Fisnik
    et al.
    Norwegian University of Science and Technology, Norway.
    Yayilgan, S. Y.
    Norwegian University of Science and Technology, Norway.
    Security and Privacy Considerations for IoT Application on Smart Grids: Survey and Research Challenges2016Inngår i: 2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW), 2016, s. 63-68Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The emergence and evolution of Internet of Things (IoT) offers great advantages to improve substantially the management over electricity consumption and distribution to the benefit of consumers, suppliers and grid operators. However, introducing IoT related devices and technologies in smart grids might lead to new security and privacy challenges. Though necessary technological innovations to ensure secure communication are being developed, more work is still required towards more secure standards for communication between devices and Smart Grids. This paper provides an overview about the security and privacy challenges of IoT applications in smart grids. Furthermore, we highlight and analyze some solutions and practices being used to cope with security and privacy requirements for IoT on deployment and management of smart grid. We address three types of challenge domains: customer domain, information and communication domain, and the grid domain.

  • 13.
    Dalipi, Fisnik
    et al.
    Norwegian University of Science and Technology (NTNU), Norway.
    Yayilgan, Sule Y.
    University of Science and Technology (NTNU), Norway.
    Imran, Ali S.
    University of Science and Technology (NTNU), Norway.
    Kastrati, Zenun
    University of Science and Technology (NTNU), Norway.
    Towards Understanding the MOOC Trend: Pedagogical Challenges and Business Opportunities2016Inngår i: Learning and Collaboration Technologies. LCT 2016., Toronto: Springer, 2016, s. 281-291Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Undoubtedly, MOOCs have the potential to introduce a new wave of technological innovation in learning. In spite of the great interest among the educators and the general public MOOCs have generated, there are some challenges that MOOCs might face when it comes to examining and determining the best pedagogical approaches that MOOCs should be based on. Moreover, MOOCs are facing also challenges towards building a consistent business model. The main objective of this paper is to shed more light on the MOOCs phenomenon, by analyzing and discussing some benefits and drawbacks of MOOCs from the pedagogical and business perspectives. Therefore, in this paper we provide an in-depth analysis of MOOCs challenges and opportunities towards determining pedagogical innovations. We also analyze current trends of MOOCs expansion to create new educational markets by overpassing the bricks-and-mortar educational institutions. To do so, we conduct a SWOT analysis on MOOCs. Finally, we provide possible directions and insights for future research to better understand how MOOCs can be improved to lead to greater innovations in the higher education landscape to answer the needs of a knowledge-based economy.

  • 14.
    Dalipi, Fisnik
    et al.
    Gjøvik University College, Norway.
    Yayilgan, Sule Yildirim
    Gjøvik University College, Norway.
    The impact of environmental factors to skiing injuries: Bayesian regularization neural network model for predicting skiing injuries2015Inngår i: 2015 6th International Conference on Computing, Communication and Networking Technologies (ICCCNT), IEEE, 2015, s. 1-6, artikkel-id 35239Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Skiing is a winter sport that is found very attractive to many people. Nevertheless, this sport is considered among high-risk sports due to the potential danger of severe injury or death. This is because of variable weather and terrain conditions, obstacles including other skiers, high speeds, trees, etc. Artificial Neural Networks have many applications in predicting the occurrence of various accident severities. In this article, we study the impact of the environmental factors to potential risk factor assessment in skiing. Hence, we apply the Bayesian Regularization Back Propagation neural network (BRBP) to predict the number of severe injuries in skiing, based on the data obtained from our prototype ski-injury registration system, the estimated bindings of environmental conditions, and the potential risk for resulting number of personal injuries. Through comparing with Levenberg Marquardt Back Propagation (LMBP), in terms of prediction accuracy, our experimental results show that BRBP has better performance by achieving higher predictive accuracy.

  • 15.
    Dalipi, Fisnik
    et al.
    Gjøvik University College, Norway.
    Yayilgan, Sule Yildirim
    Gjøvik University College, Norway.
    Gebremedhin, Alemayehu
    Faculty of Technology and Management, Norway.
    A machine learning approach to increase energy efficiency in district heating systems2015Inngår i: Environmental Engineering and Computer Application: Proceedings of the International Conference on Environmental Engineering and Computer Application, ICEECA 2014, Hong kong: CRC Press, 2015, s. 223-226Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Heat demand prediction is an important part of increasing system efficiency within district heating. To achieve this efficiency, the energy provider companies need to estimate how much energy is re quired to satisfy the market demand. In this paper, we propose a method to investigate the application of online ma chine learning algorithm to achieve energy efficiency and optimization in District Heating (DH) systems by predicting the heat demand on the consumer side. To accomplish this, we are planning to use operational data from a Norwegian company (EffektivEnergi AS, Hamar) for a group of buildings that are connected to DH in other places.

  • 16.
    Dalipi, Fisnik
    et al.
    Norwegian University of Science and Technology, Norway.
    Yayilgan, Sule Yildirim
    Norwegian University of Science and Technology, Norway.
    Gebremedhin, Alemayehu
    Norwegian University of Science and Technology, Norway.
    Data-Driven Machine Learning Model in District Heating System for Heat Load Prediction: A Comparison Study2016Inngår i: Applied Computational Intelligence and Soft Computing, ISSN 1687-9724, E-ISSN 1687-9732, artikkel-id 3403150Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We present our data-driven supervised machine-learning (ML) model to predict heat load for buildings in a district heating system (DHS). Even though ML has been used as an approach to heat load prediction in literature, it is hard to select an approach that will qualify as a solution for our case as existing solutions are quite problem specific. For that reason, we compared and evaluated three ML algorithms within a framework on operational data from a DH system in order to generate the required prediction model. The algorithms examined are Support Vector Regression (SVR), Partial Least Square (PLS), and random forest (RF). We use the data collected from buildings at several locations for a period of 29 weeks. Concerning the accuracy of predicting the heat load, we evaluate the performance of the proposed algorithms using mean absolute error (MAE), mean absolute percentage error (MAPE), and correlation coefficient. In order to determine which algorithm had the best accuracy, we conducted performance comparison among these ML algorithms. The comparison of the algorithms indicates that, for DH heat load prediction, SVR method presented in this paper is the most efficient one out of the three also compared to other methods found in the literature.

  • 17.
    Dalipi, Fisnik
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap (DV). Gjovik University College, Norway.
    Yayilgan, Sule Yildirim
    Gjovik University College, Norway.
    Kastrati, Zenun
    Gjovik University College, Norway.
    Enhancing the Learner’s Performance Analysis Using SMEUS Semantic E-learning System and Business Intelligence Technologies2015Inngår i: Learning and Collaboration Technologies. LCT 2015, Los Angeles: Springer, 2015, s. 208-217Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Ontologies represent an efficient way of semantic web application on e-learning and offer great opportunity by bringing great advantages to e-learning systems. Nevertheless, despite the many advantages that we get from using ontologies, in terms of structuring the data, there are still many unresolved problems related to the difficulties about getting proper information about a learner’s behavior. Consequently, there is a need of developing tools that enable analysis of the learner’s interaction with the e-learning environment. In this paper, we propose a framework for the application of Business Intelligence (BI) and OLAP technologies in SMEUS e-learning environment. Hence, on one hand, the proposed framework will enable and support the decision-making by answering some questions related to learner’s performance, and on the other hand, will present a case study model for implementing these technologies into a semantic e-learning environment.

  • 18.
    Dalipi, Fisnik
    et al.
    Gjovik University College, Norway.
    Yayilgan, Sule Yilidrim
    Gjøvik University College, Norway.
    Gebremedhin, Alemayehu
    Gjøvik University College, Norway.
    A Cloud Computing Framework for Smarter District Heating Systems2015Inngår i: 2015 IEEE 12th Intl Conf on Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom), IEEE, 2015, s. 1413-1416Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Nowadays, EU is supporting various projects to motivate and support citizen’s behavioral to achieve greater energy efficiency in district heating systems by taking advantage of ICT while ensuring energy savings from this new ICT-enabled solutions are greater than the cost for the provision of the services. Modern heating networks requires tools for constant monitoring and control of the network to ensure high effectiveness and reliability. Therefore, a flexible and efficient distributed data collection and storage, that operates with diverse sensors and via different types of networks is required. Moreover, such a system needs to be highly dependable, and separate parts of the system should operate even if the communication is lost. Cloud computing has an answer for this enormous network of computing resources and storage needs, since it has several good properties such as being energy saving, cost saving, agile, scalable, and flexible. In this paper, we propose a cloud computing based framework that integrates all the required advanced communication technologies to create an intelligent district heating network.

  • 19.
    Dika, Agni
    et al.
    South East European University, Macedonia.
    Bilali, Kusthrim
    Tetovo State University, Macedonia.
    Dalipi, Fisnik
    Tetovo State University, Macedonia.
    Implementing and using new e-testing system to increase the effectiveness of learning in primary schools of Macedonia2012Inngår i: 2012 International Conference on Education and e-Learning Innovations (ICEELI), 2012, s. 1-4Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Nowadays, the impact of technology on education has been outstanding and this brings new challenges for educational institutions to manage many issues that were previously not managed with ease due to geographical limitations or lack of adequate training technologies. The extensive use of technology in learning makes its use inevitable in the assessment process. Although, a lot of software packages exist in the market, it is difficult to adapt them according to a certain educational system. In this paper we present the characteristics of the new model of e-testing system that we have designed and developed. This system is implemented and is used for testing by several schools of our country. Before applying the new system, students were tested in a classical way. We have gathered and compared the classical testing results and those from using e-testing tool for assessment of student knowledge. As a conclusion, the success of the students tested electronically is much higher comparing with the success of students tested classically.

  • 20.
    Idrizi, Florim
    et al.
    Tetovo State University, Macedonia.
    Rustemi, Avni
    Tetovo State University, Macedonia.
    Dalipi, Fisnik
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV). Tetovo State University, Macedonia.
    A new modified sorting algorithm: A comparison with state of the art2017Inngår i: 2017 6th Mediterranean Conference on Embedded Computing (MECO), IEEE, 2017, s. 419-424Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Choosing the right method to sort numbers has a huge effect on how quickly a computer can process a task. The most used sorting algorithms today have been discovered years ago, and to this day, they have been the best for the job as there was no other competitive algorithm. Through this paper, we make an analysis and comparison between the state of the art algorithms in sorting and based on their analogy of functionality, we propose a new modified sorting algorithm. We then present a brief description of the new modified algorithm, conduct comparisons with the state of the art, and finally we give conclusions about the performance of the proposed algorithm versus the most popular sorting algorithms. Moreover, we highlight the benefits of using this algorithm in different fields by various business companies or software developers, in cases when they need faster and easier sorting for their data management.

  • 21.
    Imran, Ali Shariq
    et al.
    Norwegian University of Science and Technology (NTNU), Norway.
    Dalipi, Fisnik
    University of South-Eastern Norway, Norway.
    Kastrati, Zenun
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Predicting Student Dropout in a MOOC: An Evaluation of a Deep Neural Network Model2019Inngår i: Proceedings of the 2019 5th International Conference on Computing and Artificial Intelligence, ACM Publications, 2019, s. 190-195Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Massive Open Online Courses (MOOCs) have transformed the way educational institutions deliver high-quality educational material to the onsite and distance learners across the globe. As a result, a new paradigm shifts as to how learners acquire and benefit from the wealth of knowledge provided by a MOOC at their doorstep nowadays in contrast to the brick and mortar settings is visible. Learners are therefore showing a profound interest in the MOOCs offered by top universities and industry giants. They have also attracted a vast number of students from far-flung areas of the world. The massive number of registered students in MOOCs, however, pose one major challenge, i.e., 'the dropouts'. Course planners and content providers are struggling to retain the registered students, which give rise to a new research agenda focusing on predicting and explaining student dropout and low completion rates in a MOOC. Machine learning techniques utilizing deep learning approaches can efficiently predict the potential dropouts and can raise an alert well before time. In this paper, we have focused our study on the application of feed-forward deep neural network architectures to address this problem. Our model achieves not only high accuracy, but also low false negative rate while predicting dropouts on the MOOC data. Moreover, we also provide an in-depth comparison of the proposed architectures concerning precision, recall, and F1 measure.

  • 22.
    Imran, Ali Shariq
    et al.
    Norwegian University of Science and Technology (NTNU), Norway.
    Pireva, Krenare
    University of SheffieldSheffield, UK.
    Dalipi, Fisnik
    Norwegian University of Science and Technology (NTNU), Norway.
    Kastrati, Zenun
    Norwegian University of Science and Technology (NTNU), Norway.
    An Analysis of Social Collaboration and Networking Tools in eLearning2016Inngår i: Learning and Collaboration Technologies. LCT 2016 / [ed] Zaphiris P., Ioannou A., Springer, 2016, s. 332-343Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Many online learning websites and learning management systems (LMS) provide social collaboration and networking tools to aid learning and to interact with peers for knowledge sharing. The benefit of collaborating with each other is certainly undeniable, such tools, however, can be a distraction from the actual tasks for learners. The paper presents a study on social media tools supported by various eLearning systems to understand the impact on students learning activities. A survey questionnaire is designed for this purpose. The data is collected from students who have had experience using different massive open online course (MOOC) eLearning platforms and LMS from various universities. The results of the survey indicate that more than 95 % of the participants use at least one of the social tools in their daily life activities, and almost 84 % of them have used these tools in connection with the eLearning systems. It is also interesting to note that 92 % of the participants intend to use social tools for study purposes. The results indicate that there is a need to integrate more of these social media tools into eLearning systems.

  • 23.
    Kastrati, Zenun
    et al.
    GjøVik University College, Norway.
    Imran, Ali Shariq
    GjøVik University College, Norway.
    Yildirim-Yayilgan, Sule
    GjøVik University College, Norway.
    Dalipi, Fisnik
    GjøVik University College, Norway.
    Analysis of Online Social Networks Posts to Investigate Suspects Using SEMCON2015Inngår i: Social Computing and Social Media. SCSM 2015, Los Angeles: Springer, 2015, s. 148-157Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Analysing users’ behaviour and social activity for investigating suspects is an area of great interest nowadays, particularly investigating the activities of users on Online Social Networks (OSNs) for crimes. The criminal activity analysis provides a useful source of information for law enforcement and intelligence agencies across the globe. Current approaches dealing with the social criminal activity analysis mainly rely on the contextual analysis of data using only co-occurrence of terms appearing in a document to find the relationship between criminal activities in a network. In this paper, we propose a model for automated social network analysis in order to assist law enforcement and intelligence agencies to predict whether a user is a possible suspect or not. The model uses web crawlers suited to retrieve users’ data such as posts, feeds, comments, etc., and exploits them semantically and contextually using an ontology enhancement objective metric SEMCON. The output of the model is a probability value of a user being a suspect which is computed by finding the similarity between the terms obtained from the SEMCON and the concepts of criminal ontology. An experiment on analysing the public information of 20 Facebook users is conducted to evaluate the proposed model.

  • 24.
    Kurti, Arianit
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap (DV).
    Dalipi, Fisnik
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap (DV). Linnaeus University.
    Bridging the Gap between Academia and Industry: Lessons Learned from a Graduate IT Professional Development Program2017Inngår i: Abstract Book: 2nd Annual International Conference on Engineering Education & Teaching, 5-8 June 2017, Athens, Greece / [ed] Gregory T. Papanikos, Athens, 2017, s. 27-27Konferansepaper (Annet vitenskapelig)
    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. 

  • 25.
    Pireva, Krenare
    et al.
    The University of Sheffield, UK.
    Imran, Ali Sharia
    Gjøvik University College, Norway.
    Dalipi, Fisnik
    Gjøvik University College, Norway.
    User behaviour analysis on LMS and MOOC2015Inngår i: 2015 IEEE Conference on  e-Learning, e-Management and e-Services (IC3e), IEEE, 2015, s. 21-26Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper presents results of a subjective experiment of user behaviour analysis on state-of-the-art learning management systems (LMS) and massive open online courses (MOOCs). The purpose of this study is to conduct a usability analysis on different eLearning platforms by observing subjects facial expressions, and based on the generated results to speculate which of the platforms are easy to use and work with for a new user. An experiment is designed for this purpose with different tasks that each subject has to perform, while they are being recorded. The facial recordings are analysed to find seven emotional engagement attributes and three sentiment engagement attributes using facial expression software. The results of our work show some very interesting findings. Additionally we have also proposed some recommendations based on an extensive comparison of features among different LMS that will provide better content personalization and customization, thereby improving learning outcome.

  • 26.
    Salah Uddin, Ahmed
    et al.
    University of South-Eastern Norway, Norway.
    Aasnæs, Steinar
    University of South-Eastern Norway, Norway.
    Dalipi, Fisnik
    University of South-Eastern Norway, Norway.
    Hesten, Knut
    University of South-Eastern Norway, Norway.
    Analytics-driven digital platform for regional growth and development: a case study from Norway2019Inngår i: ICDS 2019, The Thirteenth International Conference on Digital Society and eGovernments / [ed] Lasse Berntzen, International Academy, Research and Industry Association (IARIA), 2019, s. 56-62, artikkel-id icds_2019_3_30_10048Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper, we present the growth barometer (Vekstbarometer in Norwegian), which is a digital platform that provides the development trends in the regional context in a visual and user-friendly way. The platform is developed to use open data from different sources that is presented mainly in five main groups: goals, premises or prerequisites for growth, industries, growth, and expectations. Furthermore, it also helps to improve decision-making and transparency, as well as provide new knowledge for research and society. The platform uses sensitive and non-sensitive open data. In contrast to other similar digital platforms from Norway, where the data is presented as raw data or with basic level of presentations, our platform is advantageous since it provides a range of options for visualization that makes the statistics more comprehensive.

  • 27.
    Yayilgan, Sule Yildirim
    et al.
    Gjøvik University College, Norway.
    Arntzen, Aurilla A.
    Buskerud and Vestfold University College, Norway.
    Stavseng, Gry Helene
    Athene Prosjektledelse, Norway.
    Ljubicic, Milena
    University of Banja Luka, Bosni and Herzegovina.
    Solvang, Björn
    Narvik University College, Norway.
    Meadow, Richard
    Norwegian University of Life Sciences and Bioforsk, Norway.
    Dalipi, Fisnik
    Gjøvik University College, Norway.
    Knowledge, Technology and Innovation (KTI): Opportunities, issues and challenges of KTI transfer between Norway and the Balkans countries2015Inngår i: 2015 International Conference on Information Technology Based Higher Education and Training (ITHET), IEEE, 2015, s. 1-7Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Several studies have shown that Knowledge, Technologies, and Innovation play an important role in fostering a country’s development. Education is the backbone for a sustainable and competitive economy. Although, the Balkans as a middle-income region has experienced growth since the late 1990s, the region is still facing many challenges. Norway, through the HERD program funded by the Norwegian Ministry of Foreign Affairs, is providing support to make the Balkan economy more competitive by providing mechanisms facilitating knowledge and technology building. This paper reports the experience of five funded projects. Opportunities and challenges are discussed in order to develop a general framework facilitating the economic growth in Balkan countries.

  • 28.
    Yayilgan, Sule Yildirim
    et al.
    Gjøvik University Colleg, Norway.
    Du, Yang
    Gjøvik University Colleg, Norway.
    Dalipi, Fisnik
    Gjøvik University Colleg, Norway.
    Jeppesen, Jonas
    Scandinavian Ski Safety Institute, Zyberia AS, Norway.
    A novel system architecture for efficient management of skiing injuries2015Inngår i: Proceedings of 2015 International Conference on Interactive Mobile Communication Technologies and Learning, IMCL 2015,  December 2015, IEEE, 2015, s. 73-77, artikkel-id 7359558Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Mobile applications and the emergence of cloud computing are considered as main drivers of extending the scope of health services and empowering the eHealth, resulting in a new branch developed very rapidly in recent years, named mHealth, the use of mobile applications for healthcare. In this paper, we propose a system architecture for ski injury registration. Our research work is inspired by the need of integrating mHealth apps in managing skiing injuries to provide higher healthcare service quality and faster availability of data. Our approach focuses both on the design of interfaces for mobile devices and presenting an architecture for the digital ski injury registration system. The design of the registration system is intended to greatly simplify the workflow between ski patrollers and the medical centers and help improve healthcare services. By the use of this system, the ski patroller will be able to provide some useful information to the doctors at the hospital in advance and in a timely manner. We employ user-centered design while developing the mobile interfaces for the ski patrollers, the nurses and the doctors. We conducted a test of a pilot of the ski patroller system in collaboration with the ski patroller in Trysil, Norway. The test had two-evaluation points and based on the results of the tests, we obtained implications for improving the design of mobile interfaces for the proposed architecture.

  • 29.
    Yildirim-Yayilgan, Sule
    et al.
    NTNU, Norway.
    Du, Yang
    NTNU, Norway.
    Dalipi, Fisnik
    NTNU, Norway.
    Jeppesen, Jonas C.
    A New Ski Injury Registration System Architecture Using Mobile Applications to Enhance Skiing Safety2016Inngår i: International Journal of Interactive Mobile Technologies (iJIM), ISSN 1865-7923, E-ISSN 1865-7923, Vol. 10, nr 4Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Mobile apps play an increasingly important role in healthcare institutions by enhancing the quality of healthcare services. Their role in sport injury prevention is also instrumental. In this article, we propose a system architecture for ski injury registration using mobile apps. Our work follows the idea of integrating and using mHealth apps to manage skiing injuries and to provide higher healthcare service quality and faster availability of data. With this work, we aim to greatly simplify the information workflow between the ski patrollers and the medical centers. Having the right information in the right place and on the right time for the injured person, the ski patroller then delivers to the medical centers that information in a format that is easy to analyze by the medical personnel and be prepared for possible interventions. To develop the mobile interfaces for the ski patrollers, nurses and doctors, we employ user-centered design. The overall system features and implementation are also explained and described in this paper. For evaluation purposes of our proposed system architecture, we have conducted a traditional user test of the ski patroller system in collaboration with the ski patrollers in the ski resort of Trysil in Norway. Moreover, a heuristic evaluation with four evaluators is also conducted. The traditional test had two-evaluation points and based on the results of the tests, we obtained implications for enhancing the design of mobile interfaces for the proposed architecture.

1 - 29 of 29
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