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  • 1.
    Abd-Ellah, Mahmoud Khaled
    et al.
    Electronics and Communications Department, Al-Madina Higher Institute for Engineering and Technology, Giza, Egypt.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems. Faculty of Engineering, Al-Alzhar University, P.O. Box 83513, Qena, Egypt.
    Hamed, Hesham F. A.
    Department of Telecommunications Eng., Egyptian Russian University, Cairo, Egypt. Department of Communications and Electronics, Faculty of Engineering, Minia University, Minia, Egypt.
    Khalaf, Ashraf A. M.
    Department of Communications and Electronics, Faculty of Engineering, Minia University, Minia, Egypt.
    Parallel Deep CNN Structure for Glioma Detection and Classification via Brain MRI Images2019In: IEEE-ICM 2019 CAIRO-EGYPT: The 31st International Conference on Microelectronics, IEEE, 2019, p. 304-307Conference paper (Other academic)
    Abstract [en]

    Although most brain tumor diagnosis studies have focused on tumor segmentation and localization operations, few studies have focused on tumor detection as a time- and effort-saving process. This study introduces a new network structure for accurate glioma tumor detection and classification using two parallel deep convolutional neural networks (PDCNNs). The proposed structure is designed to identify the presence and absence of a brain tumor in MRI images and classify the type of tumor images as high-grade gliomas (HGGs, i.e., glioblastomas) or low-grade gliomas (LGGs). The introduced PDCNNs structure takes advantage of both global and local features extracted from the two parallel stages. The proposed structure is not only accurate but also efficient, as the convolutional layers are more accurate because they learn spatial features, and they are efficient in the testing phase since they reduce the number of weights, which reduces the memory usage and runtime. Simulation experiments were accomplished using an MRI dataset extracted from the BraTS 2017 database. The obtained results show that the proposed parallel network structure outperforms other detection and classification methods in the literature.

  • 2.
    Abd-Ellah, Mahmoud Khaled
    et al.
    Al-Madina Higher Institute for Engineering and Technology.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Khalaf, Ashraf A. M.
    Minia University, Egypt.
    Hamed, Hesham F. A.
    Minia University, Egypt.
    Classification of Brain Tumor MRIs Using a Kernel Support Vector Machine2016In: Building Sustainable Health Ecosystems: 6th International Conference on Well-Being in the Information Society, WIS 2016, Tampere, Finland, September 16-18, 2016, Proceedings / [ed] Hongxiu Li, Pirkko Nykänen, Reima Suomi, Nilmini Wickramasinghe, Gunilla Widén, Ming Zhan, Springer International Publishing , 2016, p. 151-160Conference paper (Refereed)
    Abstract [en]

    The use of medical images has been continuously increasing, which makes manual investigations of every image a difficult task. This study focuses on classifying brain magnetic resonance images (MRIs) as normal, where a brain tumor is absent, or as abnormal, where a brain tumor is present. A hybrid intelligent system for automatic brain tumor detection and MRI classification is proposed. This system assists radiologists in interpreting the MRIs, improves the brain tumor diagnostic accuracy, and directs the focus toward the abnormal images only. The proposed computer-aided diagnosis (CAD) system consists of five steps: MRI preprocessing to remove the background noise, image segmentation by combining Otsu binarization and K-means clustering, feature extraction using the discrete wavelet transform (DWT) approach, and dimensionality reduction of the features by applying the principal component analysis (PCA) method. The major features were submitted to a kernel support vector machine (KSVM) for performing the MRI classification. The performance evaluation of the proposed system measured a maximum classification accuracy of 100 % using an available MRIs database. The processing time for all processes was recorded as 1.23 seconds. The obtained results have demonstrated the superiority of the proposed system.

  • 3.
    Abd-Ellah, Mahmoud Khaled
    et al.
    Al-Madina Higher Institute for Engineering and Technology, Giza, Egypt .
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems. Faculty of Engineering, Al-Azhar University, Qena, Egypt.
    Khalaf, Ashraf A. M.
    Minia University, Minia, Egypt .
    Hamed, Hesham F. A.
    Egyptian Russian University, Cairo, Egypt. Minia University, Minia, Egypt .
    Deep Convolutional Neural Networks: Foundations and Applications in Medical Imaging2020In: Deep Learning in Computer Vision: Principles and Applications / [ed] Mahmoud Hassaballah, Ali Ismail Awad, CRC Press, 2020, 1st, p. 233-260Chapter in book (Other academic)
  • 4.
    Abd-Ellah, Mahmoud Khaled
    et al.
    Electronic and Communication Department Al-Madina Higher Institute for Engineering and Technology, Giza.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Khalaf, Ashraf A. M.
    Faculty of Engineering, Minia University.
    Hamed, Hesham F. A.
    Faculty of Engineering, Minia University.
    Design and implementation of a computer-aided diagnosis system for brain tumor classification2017In: 2016 28th International Conference on Microelectronics (ICM), 2017, p. 73-76, article id 7847911Conference paper (Refereed)
    Abstract [en]

    Computer-aided diagnosis (CAD) systems have become very important for the medical diagnosis of brain tumors. The systems improve the diagnostic accuracy and reduce the required time. In this paper, a two-stage CAD system has been developed for automatic detection and classification of brain tumor through magnetic resonance images (MRIs). In the first stage, the system classifies brain tumor MRI into normal and abnormal images. In the second stage, the type of tumor is classified as benign (Noncancerous) or malignant (Cancerous) from the abnormal MRIs. The proposed CAD ensembles the following computational methods: MRI image segmentation by K-means clustering, feature extraction using discrete wavelet transform (DWT), feature reduction by applying principal component analysis (PCA). The two-stage classification has been conducted using a support vector machine (SVM). Performance evaluation of the proposed CAD has achieved promising results using a non-standard MRIs database.

  • 5.
    Abd-Ellah, Mahmoud Khaled
    et al.
    Electronics and Communications Department, Al-Madina Higher Institute for Engineering and Technology, Giza, Egypt.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Faculty of Engineering, Al-Azhar University, Qena, Egypt.
    Khalaf, Ashraf A.M.
    Electronics and Communications Department, Faculty of Engineering, Minia University, Minia, Egypt.
    Hamed, Hesham F.A.
    Electronics and Communications Department, Faculty of Engineering, Minia University, Minia, Egypt.
    A Review on Brain Tumor Diagnosis from MRI Images: Practical Implications, Key Achievements, and Lessons Learned2019In: Magnetic Resonance Imaging, ISSN 0730-725X, E-ISSN 1873-5894, Vol. 61, p. 300-318Article in journal (Refereed)
    Abstract [en]

    The successful early diagnosis of brain tumors plays a major role in improving the treatment outcomes and thus improving patient survival. Manually evaluating the numerous magnetic resonance imaging (MRI) images produced routinely in the clinic is a difficult process. Thus, there is a crucial need for computer-aided methods with better accuracy for early tumor diagnosis. Computer-aided brain tumor diagnosis from MRI images consists of tumor detection, segmentation, and classification processes. Over the past few years, many studies have focused on traditional or classical machine learning techniques for brain tumor diagnosis. Recently, interest has developed in using deep learning techniques for diagnosing brain tumors with better accuracy and robustness. This study presents a comprehensive review of traditional machine learning techniques and evolving deep learning techniques for brain tumor diagnosis. This review paper identifies the key achievements reflected in the performance measurement metrics of the applied algorithms in the three diagnosis processes. In addition, this study discusses the key findings and draws attention to the lessons learned as a roadmap for future research.

  • 6.
    Abd-Ellah, Mahmoud Khaled
    et al.
    Electronics and Communications Department, Al-Madina Higher Institute for Engineering and Technology, Giza, Egypt.
    Khalaf, Ashraf A. M.
    Faculty of Engineering, Minia University, Minia, Egypt.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems. Faculty of Engineering, Al-Azhar University, Qena, Egypt.
    Hamed, Hesham F. A.
    Faculty of Engineering, Minia University, Minia, Egypt.
    TPUAR-Net: Two Parallel U-Net with Asymmetric Residual-Based Deep Convolutional Neural Network for Brain Tumor Segmentation2019In: Image Analysis and Recognition: 16th International Conference, ICIAR 2019, Waterloo, ON, Canada, August 27–29, 2019, Proceedings, Part II / [ed] Fakhri Karray, Aurélio Campilho, Alfred Yu, Springer, 2019, p. 106-116Conference paper (Refereed)
    Abstract [en]

    The utilization of different types of brain images has been expanding, which makes manually examining each image a labor-intensive task. This study introduces a brain tumor segmentation method that uses two parallel U-Net with an asymmetric residual-based deep convolutional neural network (TPUAR-Net). The proposed method is customized to segment high and low grade glioblastomas identified from magnetic resonance imaging (MRI) data. Varieties of these tumors can appear anywhere in the brain and may have practically any shape, contrast, or size. Thus, this study used deep learning techniques based on adaptive, high-efficiency neural networks in the proposed model structure. In this paper, several high-performance models based on convolutional neural networks (CNNs) have been examined. The proposed TPUAR-Net capitalizes on different levels of global and local features in the upper and lower paths of the proposed model structure. In addition, the proposed method is configured to use the skip connection between layers and residual units to accelerate the training and testing processes. The TPUAR-Net model provides promising segmentation accuracy using MRI images from the BRATS 2017 database, while its parallelized architecture considerably improves the execution speed. The results obtained in terms of Dice, sensitivity, and specificity metrics demonstrate that TPUAR-Net outperforms other methods and achieves the state-of-the-art performance for brain tumor segmentation.

  • 7.
    Ahmadzadegan, M. Hossein
    et al.
    Azad University, Tehran, Iran.
    Ghorbani, Hamidreza
    Azad University, Tehran, Iran.
    Ståhlbröst, Anna
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems.
    Security-Centric Investigation of Social Networks and Preventative Behavioral Analysis of Online Activity by the Kuleshov effect2020In: 2020 IEE 9th International Conference on Communication Systems and Network Technologies, IEEE, 2020, p. 271-276Conference paper (Refereed)
    Abstract [en]

    The Internet beside providing many advantages has some disadvantages. The full unfamiliarity with cyberspace can bring harms and inconvenience to families. This study attempted to introduce the disadvantages and threats on the Internet and present some countermeasures to decrease such threats and harms. Social networks are currently so epidemic that even many companies and organizations formally supply the internal communication system among their members and employees through this social networks and the number of the users of such networks is increasing daily. The term “information security” covers a broad spectrum of activities in an organization. Information security means preventing the unauthorized access to information and products or apply some changes or delete such information using a series of processes. Such actions can be considered as a protection package against current resources in different situations (e.g., a hacker attacks which occurs a lot) by those in charge of information security. One of the most important issues which is considered as a security challenge in these networks is the security and retention of the data and information shared by users from unauthorized access and unwanted disclosure. In this article the Kuleshov effect from cinema has been deployed to explain and launch a behavioral analysis of online activities.

  • 8.
    Ahmer, Muhammad
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements. AB SKF, Gothenburg, Sweden.
    Marklund, Pär
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.
    Gustafsson, Martin
    AB SKF, Gothenburg, Sweden.
    Berglund, Kim
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.
    An implementation framework for condition-based maintenance in a bearing ring grinder2022In: Leading manufacturing systems transformation – Proceedings of the 55th CIRP Conference on Manufacturing Systems 2022 / [ed] Emanuele Carpanzano, Claudio Boër, Anna Valente, Elsevier, 2022, Vol. 107, p. 746-751Conference paper (Refereed)
    Abstract [en]

    The demand on a bearing ring grinder, as any other machine tool, is to produce parts as per the specification and desired quality. A failure to achieve the quality can be due to functional issues or mechanical failure modes. Ultimately this results in lower productivity and higher production costs. Despite the increased emphasis on practicing condition-based machine maintenance (CBM) in manufacturing applications, it is still considered a challenge to fully deploy CBM in production machines due to diversity in equipment and variety in machine configurations as well as complex characteristics of failure modes. Although there exists extensive literature on CBM for machine tools and subsystems, the issue remains with realization of a technically capable and cost effective CBM system, specifically for a bearing ring grinder. Therefore, sensor(s) selection, data acquisition setup, data processing and analysis are the essential factors considered in the proposed framework to ensure a systematic and organized CBM implementation. The CBM setup is evaluated against production of bearing rings under different process and failure conditions. A machine type independent data acquisition system is designed to capture both machine and process dynamics. The data gathered from sensors at strategic locations exhibits its effectiveness in capturing the process and condition variations in relation to time and operating modes. The presented results of data analysis support the capability and effectiveness of the proposed framework. The utility of this framework can be extended for any number of scenarios including predictive maintenance or adaptive process optimization where solutions using machine learning and artificial intelligence tools can benefit from high dimensional structured dataset. The proposed framework provides a strong foundation to fast track the adaption of CBM in other production machines having similar subsystems.

  • 9.
    AL-Hilfi, Mohammed
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering. Luleå tekniska universitet, Institutionen för system- och rymdteknik.
    Olovsson, Emil
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering. Luleå tekniska universitet, Institutionen för system- och rymdteknik.
    Integration & Interoperabilitet vid utveckling av IT-system2017Independent thesis Basic level (degree of Bachelor), 180 HE creditsStudent thesis
    Abstract [en]

    This study will increase understanding of how a system developer can solve complex problems within organizations by developing a new information technology system (IT-system), with a focus on technical- and organizational interoperability at the integration process. The authors act as system developers through a case study where there is a need for a new IT-system.

    In this thesis an abductive approach is used combined with an instrumental case study. The work is split up into four phases:

    (1) Identifying problems within the organization by drawing up business models, collecting data through qualitative semi-structured interviews with stakeholders, and the development of a theoretical base. As theoretical frame of reference Integration and interoperability (I & I) is defined, business models are explained, how technical- and operational interoperability differs, how business models are created, agile software development and usability of IT-systems.

    (2) Building, intervention and evaluation. The IT-system is built using an iterative and incremental software development process where focus is on solving the identified problems. During the development stage requirements and challenges are identified to create the business model target view. The IT-system is developed to reflect this view where each iteration of the IT-system is revised from flaws discovered during interviews with stakeholders. The first iteration did not fulfill the stakeholders’ requirements and expectations, but later iterations succeeded in this and were implemented within the organization. When the IT-system had been implemented, it was evaluated by the end users to identify if the system developers had succeeded in solving the organizational problems, and to check usability of the IT-system.

    (3) Reflection and learning. The result is analyzed and discussed, compared to the theoretical frame of reference and course of action. The result shows that system developers succeeded in identifying complex problems within the organization and managed to create a new IT-system that met stakeholders’ needs, while also solving identified organizational problems.

    (4) In the last phase formalization of learning are general concepts compiled that can be used in other projects. In this thesis are eight aspects and principles are identified that can be used by system developers when developing IT-systems.

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  • 10.
    Ali, Bako
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Faculty of Engineering, Al Azhar University.
    Cyber and Physical Security Vulnerability Assessment for IoT-Based Smart Homes2018In: Sensors, E-ISSN 1424-8220, Vol. 18, no 3, article id 817Article in journal (Refereed)
    Abstract [en]

    The Internet of Things (IoT) is an emerging paradigm focusing on the connection of devices, objects, or “things” to each other, to the Internet, and to users. IoT technology is anticipated to become an essential requirement in the development of smart homes, as it offers convenience and efficiency to home residents so that they can achieve better quality of life. Application of the IoT model to smart homes, by connecting objects to the Internet, poses new security and privacy challenges in terms of the confidentiality, authenticity, and integrity of the data sensed, collected, and exchanged by the IoT objects. These challenges make smart homes extremely vulnerable to different types of security attacks, resulting in IoT-based smart homes being insecure. Therefore, it is necessary to identify the possible security risks to develop a complete picture of the security status of smart homes. This article applies the operationally critical threat, asset, and vulnerability evaluation (OCTAVE) methodology, known as OCTAVE Allegro, to assess the security risks of smart homes. The OCTAVE Allegro method focuses on information assets and considers different information containers such as databases, physical papers, and humans. The key goals of this study are to highlight the various security vulnerabilities of IoT-based smart homes, to present the risks on home inhabitants, and to propose approaches to mitigating the identified risks. The research findings can be used as a foundation for improving the security requirements of IoT-based smart homes.

  • 11.
    Al-Serafi, Ayman
    et al.
    Teradata Corporation.
    Elragal, Ahmed
    Department of Business Informatics and Operations, German University in Cairo (GUC), Cairo.
    Visual trajectory pattern mining: An exploratory study in baggage handling systems2014In: Advances in data mining: Advances in data mining : applications and theoretical aspects : 14th Industrial Conference, ICDM 2014, St. Petersburg, Russia, July 16-20, 2014. Proceedings / [ed] Petra Perner, Cham: Encyclopedia of Global Archaeology/Springer Verlag, 2014, p. 159-173Conference paper (Refereed)
    Abstract [en]

    There is currently a huge amount of data being collected about movements of objects. Such data is called spatiotemporal data and paths left by moving-objects are called trajectories. Recently, researchers have been targeting those trajectories for extracting interesting and useful knowledge by means of pattern analysis and data mining. But, it is difficult to analyse huge datasets of trajectories without summarizing them and visualizing them for the knowledge seeker and for the decision makers. Therefore, this research paper focuses on utilizing visual techniques and data mining analysis of trajectory patterns in order to help extract patterns and knowledge in an interactive approach. The research study proposes a research framework which integrates multiple data analysis and visualization techniques in a coherent architecture in support of interactive trajectory pattern visualization for the decision makers. An application case-study of the techniques is conducted on an airport's baggage movement data within the Baggage Handling System (BHS). The results indicate the feasibility of the approach and its methods in visually analysing trajectory patterns in an interactive approach which can support the decision maker. © 2014 Springer International Publishing Switzerland.

  • 12.
    Amin, Marian H.
    et al.
    Faculty of Management Technology, German University in Cairo, Cairo, Egypt.
    Mohamed, Ehab K.A
    Faculty of Management Technology, German University in Cairo, Cairo, Egypt.
    Elragal, Ahmed
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems.
    Corporate Disclosure via Social Media: A Data Science Approach2020In: Online information review (Print), ISSN 1468-4527, E-ISSN 1468-4535, Vol. 44, no 1, p. 278-298Article in journal (Refereed)
    Abstract [en]

    Purpose - The aim of this paper is to investigate corporate financial disclosure via Twitter among the top listed 350 companies in the UK as well as identify the determinants of the extent of social media usage to disclose financial information.

    Design/methodology/approach – This study applies an unsupervised machine learning technique, namely, Latent Dirichlet Allocation (LDA) topic modeling to identify financial disclosure tweets. Panel, Logistic, and Generalized Linear Model Regressions are also run to identify the determinants of financial disclosure on Twitter focusing mainly on board characteristics.

    Findings – Topic modeling results reveal that companies mainly tweet about 12 topics, including financial disclosure, which has a probability of occurrence of about 7 percent. Several board characteristics are found to be associated with the extent of Twitter usage as a financial disclosure platform, among which are board independence, gender diversity, and board tenure.

    Originality/value – Extensive literature examines disclosure via traditional media and its determinants, yet this paper extends the literature by investigating the relatively new disclosure channel of social media. This study is among the first to utilize machine learning, instead of manual coding techniques, to automatically unveil the tweets’ topics and reveal financial disclosure tweets. It is also among the first to investigate the relationships between several board characteristics and financial disclosure on Twitter; providing a distinction between the roles of executive versus non-executive directors relating to disclosure decisions.

  • 13. Amin, Marian Hany
    et al.
    Mohamed, Ehab Kamel
    Elragal, Ahmed
    Corporate Social Responsibility disclosure via Twitter by top listed UK companies: A Data Science Approach2018Conference paper (Refereed)
  • 14.
    Amin, Marian Hany
    et al.
    The German University in Cairo.
    Mohamed, Ehab Kamel
    Elragal, Ahmed
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Financial Disclosure on Twitter by Top Listed UK Companies: A Data Science Approach2018Conference paper (Refereed)
    Abstract [en]

    Ongoing advancements in technology have changed dramatically the disclosure media that companies adopt. Such disclosure media have evolved from the traditional paper-based ones, to the internet as the new platform to disclose information via companies’ designated websites. However, currently the new media for disclosures are the social media. The aim of this paper is to investigate corporate social media accounts for financial disclosure, as well as, identify its determinants. The sample of the study is comprised of the tweets posted on the Twitter accounts belonging to the FTSE 350 constituents. Topic modeling is applied to identify financial disclosure tweets and logistic regression is run to identify the determinants of financial disclosure on Twitter. Results show that companies use Twitter to make corporate disclosures and some board characteristics are found to have a significant relationship with financial disclosure.

  • 15.
    Amin, Marian Hany
    et al.
    German University in Cairo, Cairo, Egypt.
    Mohamed, Ehab Kamel
    Elragal, Ahmed
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Twitter: An emerging media for corporate disclosure2018Conference paper (Refereed)
    Abstract [en]

    Ongoing advancements in technology have changed dramatically the disclosure media that companies adopt. Such disclosure media have evolved from the traditional paper-based ones, to the internet as the new platform to disclose information via companies’ designated websites. However, currently the new media for disclosures are the social media. The aim of this paper is to investigate corporate social media accounts for financial disclosure, as well as, identify its determinants. The sample of the study is comprised of the tweets posted on the Twitter accounts belonging to the FTSE 350 constituents. Topic modeling is applied to identify financial disclosure tweets and logistic regression is run to identify the determinants of financial disclosure on Twitter. Results show that companies use Twitter to make corporate disclosures and some board characteristics are found to have a significant relationship with financial disclosure. 

  • 16.
    Andersson, Adrian
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    Designprinciper för digitala tjänster inom gruvindustrin2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [sv]

    Gruvindustrin befinner sig i en stor förändring allt eftersom digitaliseringen fortskrider. Digitaliseringen innebär att en mängd nya tekniker börjar implementeras i gruvor runt om i världen. En av dessa tekniker är att de anställda använder smartphones i arbetet. Detta medför dock problem då miljön inom gruvindustrin inte är optimal för de generella designprinciperna som finns att tillgå idag. Denna studie undersöker och utvecklar därför designprinciper som kan användas för mobila applikationer inom gruvindustrin. Studien har teori som behandlar generella designprinciper för mobila applikationer, mobila designmönster samt industri 4.0. Vidare har en kvalitativ studie genomförts i form av intervjuer med respondenter från både gruvindustrin men också personer med mångårig erfarenhet av utveckling av mobila applikationer till gruvindustrin. Kvalitativa studien genomfördes för att öka förståelsen kring kontexten som infinner sig inom gruvindustrin men också använda den expertis som finns inom området för att kunna utveckla relevanta designprinciper som kan vara till användning i praktiken. Den insamlade empirin jämfördes sedan mot teori och med hjälp av studiens analys kunde designprinciper som kan anses vara specifika för gruvindustrin identifieras. Slutsatserna visar att enkelhet är nyckeln till framgång och element såsom automatisk ifyllnad, enkel och snabb navigering, stora ikoner och användning av färger är några av de möjliga lösningar som föreslagits för att ta fram en användarvänlig applikation.   

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  • 17.
    Andersson, Ingemar
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Lindqvist, Göran
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Randers, Frode
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Preservation Services Planning: A Decision Support Framework2014Conference paper (Refereed)
    Abstract [en]

    Commercial organizations are experiencing a growing need to access business-criticaldata in the longer term of their operations. Governmental regulations as well as commercial interestsinfluence this need. Organizations are willing to procure cost-effective services to this end - servicesthat are increasingly based as public or private cloud solutions. With the advent of autonomous cloudservices comes the possibility to assemble (mix and match) preservation services in a workflowbasedservice-oriented solution. Following the interaction with information managers in (three)commercial organizations operating in different markets and after a review of current literature, wehave revealed a lack of comprehensive guidelines and decision support in service selection as part ofpreservation planning. Existing models and frameworks used for assessing the quality of preservationservices either manage performance-based features that service provider’s offer or the technicaldetails of the preservation actions themselves. In this paper we present our preservation-planningframework (Preserv-Qual) that addresses the need for decision support in the selection ofpreservation services that explicitly acknowledge the differences among aspects of information usewithin an organization. We describe the outcome from an evaluation of the framework in threecommercial organisations as a service quality assessment and decision support tool. This papershows how our framework supports the use of existing and proven methods, models and principlesfor service assessment, digital preservation and decision support.

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  • 18.
    Andersson, Ingemar
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Nilsson, Jörgen
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Lindqvist, Göran
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Lindbäck, Lena
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Runardotter, Mari
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Innovation and Design.
    Web archiving using the collaborative archiving services testbed2011In: eChallenges e2011 Conference Proceedings / [ed] Paul Cunningham; Miriam Cunningham, IIMC International Information Management Corporation , 2011Conference paper (Other academic)
    Abstract [en]

    Websites constitute one category of official records and as such should be preserved for the long term in compliance with Swedish legislation. Collaborative Archiving Services Testbed (CAST) supports actors involved in the selective web archiving process, from harvesting to the creation of an information package ready for transfer to a long-term archive at National Archives of Sweden. CAST is developed in compliance with the ISO standards Open Archival Information System (OAIS) and Producer-Archive Interface Methodology Abstract Standard (PAIMAS), and do also consider other well-known and established standards and recommendations in digital preservation area. CAST promotes cooperation, knowledge acquisition and sharing among users in an experimental step-by-step workflow, encouraging a proactive approach resulting in authority websites better adapted to digital preservation recommendations. CAST is developed at LDP Centre, a national competence centre in Sweden, within the digital preservation area.

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  • 19.
    Andersson, Joakim
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    Lundmark, Linus
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    Projektkaraktärernas koppling till de kritiska framgångsfaktorerna hos små företag i Norrbotten2021Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [sv]

    Det är i dagsläget känt att det finns en stor andel IT-projekt som misslyckas eller är utmanade. För små företag så är det viktigt att gå med ekonomisk vinst, men trots att det finns tidigare forskning på de kritiska framgångsfaktorerna som leder till framgång så är det fortfarande en utmaning att bedriva IT-projekt i allmänhet. Inriktningen i denna studie är att undersöka och skapa en förståelse för vilka framgångsfaktorer som är kritiska för olika projektkaraktärer och projektgenomföranden, samt om det finns fördelar eller nackdelar med dessa.

    Slutsatsen är att projektteamet, kommunikation, hantering av förändringar och ledning är framgångsfaktorer som är viktiga i de flesta projektgenomföranden och projektkaraktärer, där hantering av förändringar är viktigare för de små företagen jämfört med förekomsten i litteraturen.

    Fördelarna med olika projektkaraktärer handlar både om att kunna hantera de centrala framgångsfaktorer som förekommer, men även att prioritera de projekt som ger vinst och stabilitet under en god ledning. Det är fördelaktigt för små företag att välja större projekt där till exempel kunden har ansvar för ledning och resurshantering och leverantören bara har ansvar för sin enskilda resurs. Genom medvetenhet om de centrala framgångsfaktorer som kännetecknar en specifik projektkaraktär så kan man använda detta i en riskanalys tidigt i projektet, vilket innebär att man kan förutse hur man ska hantera de utmaningar som kan uppstå. Det är även fördelaktigt att tidigt i projektet veta var ansvaret ligger om projektet blir utmanat, samt vad konsekvenserna blir för leverantören och eventuell kund och slutanvändare.

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  • 20.
    Andersson, Simon
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    Forsberg, Andreas
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    Användarinvolvering för ökad medvetenhet: En studie om policyutvecklingsprocessen2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Many organisations experience the new general data protection regulation (GDPR) as difficult to understand and are unsure as to how they should formulate and communicate a policy that is complied by the organisation's employees. ePrivacy is a separate regulation that works as a compliment to GDPR and makes the regulation even more complex. The purpose of this study is to identify recommendations to formulate policies that increases likelihood that the policy is complied by the organisation's employees. The study was conducted as a case study with a participating company. In this study a policy has been developed within the context of the GDPR and ePrivacythat was then used in interviews with employees of the participating company. This was done in order to research the policy development process and handling of policies in that company. With this research, the knowledge of factors within policy development that affect the employees likelihood to comply with and be aware of the organisation's policies will increase. The recommendations that are formulated as a result of the study may be usedby developers to increase the likelihood that the organisation's policies are complied with and that the employees are more aware of the policies. The recommendations of the study is that developers should take advantage of user involvement in the policy development process. This gives the employees their chance to affect their own work and their processes themselves which will increase their self efficacy and awareness of policies.

    Download full text (pdf)
    fulltext
  • 21.
    Aristomenopoulos, Georgios
    et al.
    Institute of Communication and Computer Systems, Athens.
    Kaninis, Argyris
    VELTI SA of Software Products and Related Products and Services.
    Vlahopoulos, Panagiotis
    VELTI SA of Software Products and Related Products and Services.
    Sällström, Annika
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    Benbadis, Farid
    Thales Communications and Security.
    Papavassiliou, Symeon
    Institute of Communication and Computer Systems, Athens.
    The QUEENS experiment through TEFIS platform2012In: Testbeds and Research Infrastructure: Development of Networks and Communities: 8th International ICST Conference, TridentCom 2012, Thessanoliki, Greece, June 11-13, 2012, Revised Selected Papers / [ed] Thanasis Korakis ; Michael Zink ; Maximilian Ott, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2012, p. 394-396Conference paper (Refereed)
    Abstract [en]

    QUEENS (Dynamic Quality User Experience ENabling Mobile Multimedia Services) aims at exploiting and leveraging on the benefits and flexibility provided by a novel dynamic real-time QoE provisioning framework in order to assess and establish a new era of user-centric mobile multimedia applications. To achieve that, QUEENS utilizes and builds on the TEFIS infrastructure (EC ICT FIRE initiative) that provides a unique integrated platform for supporting efficient Future Internet service experiment and development involving different actors and heterogeneous testbeds. The TEFIS tools and facilities for designing, planning and executing QUEENS experiment, along with a QoE-aware mobile multimedia application prototype will be demonstrated, forming the trends of future internet services and experimental procedures

    Download full text (pdf)
    FULLTEXT01
  • 22.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Workshop on Emerging Aspects in Information Security2015Other (Other (popular science, discussion, etc.))
  • 23.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Communications in Computer and Information Science, Vol. 3812013Other (Other (popular science, discussion, etc.))
  • 24.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Computer Networks2011Other (Other (popular science, discussion, etc.))
    Abstract [en]

    The International Journal of Computer and Telecommunications Networking (COMNET)

  • 25.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Computers & Security2014Other (Other (popular science, discussion, etc.))
  • 26.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Concurrency and Computation: Practice and Experience2016Other (Other (popular science, discussion, etc.))
  • 27.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Health Information Science and Systems (HISS)2016Other (Other (popular science, discussion, etc.))
  • 28.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Information Sciences2013Other (Other (popular science, discussion, etc.))
  • 29.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Intelligent Systems Reference Library, Vol. 702014Other (Other (popular science, discussion, etc.))
  • 30.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: International Conference on Mobile and Ubiquitous Systems2013Other (Other (popular science, discussion, etc.))
  • 31.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: International Conference on Telecommunications2016Other (Other (popular science, discussion, etc.))
  • 32.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: International Conference on Telecommunications2016Other (Other (popular science, discussion, etc.))
  • 33.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: International Japan-Egypt Conference on Electronics, Communications and Computers2013Other (Other (popular science, discussion, etc.))
  • 34.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: International Journal of Computational Vision and Robotics. Special Issue on: "Advances in Soft Computing Techniques for Image Processing"2013Other (Other (popular science, discussion, etc.))
    Abstract [en]

    Vol. 3, No. 4

  • 35.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Pattern Recognition2014Other (Other (popular science, discussion, etc.))
    Abstract [en]

    The Journal of the Pattern Recognition Society

  • 36.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Science and Information Conference2014Other (Other (popular science, discussion, etc.))
  • 37.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Science and Information Conference2013Other (Other (popular science, discussion, etc.))
  • 38.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: SpringerPlus2015Other (Other (popular science, discussion, etc.))
  • 39.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Studies in Computational Intelligence, Vol. 6302016Other (Other (popular science, discussion, etc.))
  • 40.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: The 28th International Conference on Image and Vision Computing New Zealand (IVCNZ 2013)2013Other (Other (popular science, discussion, etc.))
  • 41.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: The 29th International Conference on Image and Vision Computing New Zealand (IVCNZ 2014)2014Other (Other (popular science, discussion, etc.))
  • 42.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: The 30th International Conference on Image and Vision Computing New Zealand ( (IVCNZ 2015)2015Other (Other (popular science, discussion, etc.))
  • 43.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: The 31st International Conference Image and Vision Computing New Zealand (IVCNZ 2016)2016Other (Other (popular science, discussion, etc.))
  • 44.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: The 49th Hawaii International Conference on System Sciences (HICSS-49)2016Other (Other (popular science, discussion, etc.))
  • 45.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Workshop on Emerging Aspects in Information Security2014Other (Other (popular science, discussion, etc.))
  • 46.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Faculty of Engineering, Al Azhar University, Qena, Egypt.
    Fast Fingerprint Orientation Field Estimation Incorporating General Purpose GPU2016In: Soft Computing Applications: Proceedings of the 6th International Workshop Soft Computing Applications (SOFA 2014) / [ed] Valentina Emilia Balas; Lakhmi C. Jain; Branko Kovačević, New York: Encyclopedia of Global Archaeology/Springer Verlag, 2016, Vol. 2, p. 891-902Conference paper (Refereed)
    Abstract [en]

    Fingerprint is one of the broadly utilized biometric traits for personal identification in both civilian and forensic applications due to its high acceptability, strong security, and low cost. Fingerprint ridge orientation is one of the global fingerprint representations that keeps the holistic ridge structure in a small storage area. The importance of fingerprint ridge orientation comes from its usage in fingerprint singular point detection, coarse level classification, and fingerprint alignment. However, processing time is an important factor in any automatic fingerprint identification system, estimating that ridge orientation image may consume long processing time. This research presents an efficient ridge orientation estimation approach by incorporating a Graphics Processing Unit (GPU) capability to the traditional pixel gradient method. The simulation work shows a significant enhancement in ridge orientation estimation time by 6.41x using a general purpose GPU in comparison to the CPU execution.

  • 47.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Fingerprint local invariant feature extraction on GPU with CUDA2013In: Informatica, ISSN 0350-5596, E-ISSN 1854-3871, Vol. 37, no 3, p. 279-284Article in journal (Refereed)
    Abstract [en]

    Driven from its uniqueness, immutability, acceptability, and low cost, fingerprint is in a forefront between biometric traits. Recently, the GPU has been considered as a promising parallel processing technology due to its high performance computing, commodity, and availability. Fingerprint authentication is keep growing, and includes the deployment of many image processing and computer vision algorithms. This paper introduces the fingerprint local invariant feature extraction using two dominant detectors, namely SIFT and SURF, which are running on the CPU and the GPU. The paper focuses on the consumed time as an important factor for fingerprint identification. The experimental results show that the GPU implementations produce promising behaviors for both SIFT and SURF compared to the CPU one. Moreover, the SURF feature detector provides shorter processing time compared to the SIFT CPU and GPU implementations.

    Download full text (pdf)
    FULLTEXT01
  • 48.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    From classical methods to animal biometrics: A review on cattle identification and tracking2016In: Computers and Electronics in Agriculture, ISSN 0168-1699, E-ISSN 1872-7107, Vol. 123, p. 423-435Article in journal (Refereed)
    Abstract [en]

    Cattle, buffalo and cow, identification has recently played an influential role towards understanding disease trajectory, vaccination and production management, animal traceability, and animal ownership assignment. Cattle identification and tracking refers to the process of accurately recognizing individual cattle and their products via a unique identifier or marker. Classical cattle identification and tracking methods such as ear tags, branding, tattooing, and electrical methods have long been in use; however, their performance is limited due to their vulnerability to losses, duplications, fraud, and security challenges. Owing to their uniqueness, immutability, and low costs, biometric traits mapped into animal identification systems have emerged as a promising trend. Biometric identifiers for beef animals include muzzle print images, iris patterns, and retinal vascular patterns. Although using biometric identifiers has replaced human experts with computerized systems, it raises additional challenges in terms of identifier capturing, identification accuracy, processing time, and overall system operability. This article reviews the evolution in cattle identification and tracking from classical methods to animal biometrics. It reports on traditional animal identification methods and their advantages and problems. Moreover, this article describes the deployment of biometric identifiers for effectively identifying beef animals. The article presents recent research findings in animal biometrics, with a strong focus on cattle biometric identifiers such as muzzle prints, iris patterns, and retinal vascular patterns. A discussion of current challenges involved in the biometric-based identification systems appears in the conclusions, which may drive future research directions.

  • 49.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Introduction to Information Security Foundations and Applications2018In: Information Security: Foundations, technologies and applications / [ed] Ali Ismail Awad and Michael Fairhurst, Institution of Engineering and Technology, 2018, , p. 432p. 3-9Chapter in book (Refereed)
    Abstract [en]

    Information security has extended to include several research directions like user authentication and authorization, network security, hardware security, software security, and data cryptography. Information security has become a crucial need for protecting almost all information transaction applications. Security is considered as an important science discipline whose many multifaceted complexities deserve the synergy of the computer science and engineering communities.

    Download full text (pdf)
    fulltext
  • 50.
    Awad, Ali Ismail
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andrzej, BialasInstitute of Innovative Technologies EMAG.
    Proceedings of the 2017 Federated Conference on Computer Science and Information Systems (FedCSIS 2017)2017Conference proceedings (editor) (Refereed)
    Abstract [en]

    https://fedcsis.org/2017/insert

1234567 1 - 50 of 719
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