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    • Benchmarking Q-learning methods for intelligent network orchestration in the edge 

      Reijonen, Joel; Opsenica, Miljenko; Kauppinen, Tero; Komu, Miika; Kjällman, Jimmy; Mecklin, Tomas; Hiltunen, Eero; Arkko, Jari; Simanainen, Timo; Elmusrati, Mohammed (IEEE, 13.05.2020)
      conferenceObject
      We benchmark Q-learning methods, with various action selection strategies, in intelligent orchestration of the network edge. Q-learning is a reinforcement learning technique that aims to find optimal action policies by ...
    • Cancer Modeling-on-a-Chip with Future Artificial Intelligence Integration 

      Fetah, Kirsten Lee; DiPardo, Benjamin J.; Kongadzem, Eve-Mary; Tomlinson, James S.; Elzagheid, Adam; Elmusrati, Mohammed; Khademhosseini, Ali; Ashammakhi, Nureddin (Wiley, 13.11.2019)
      article
      Cancer is one of the leading causes of death worldwide, despite the large efforts to improve the understanding of cancer biology and development of treatments. The attempts to improve cancer treatment are limited by the ...
    • Comparison of nomogram with machine learning techniques for prediction of overall survival in patients with tongue cancer 

      Alabi, Rasheed Omobolaji; Mäkitie, Antti A.; Pirinen, Matti; Elmusrati, Mohammed; Leivo, Ilmo; Almangush, Alhadi (Elsevier, 01.01.2021)
      article
      Background: The prediction of overall survival in tongue cancer is important for planning of personalized care and patient counselling. Objectives: This study compares the performance of a nomogram with a machine learning ...
    • Comparison of supervised machine learning classification techniques in prediction of locoregional recurrences in early oral tongue cancer 

      Alabi, Rasheed Omobolaji; Elmusrati, Mohammed; Sawazaki‐Calone, Iris; Kowalski, Luiz Paulo; Haglund, Caj; Coletta, Ricardo D.; Mäkitie, Antti A.; Salo, Tuula; Almangus, Alhadi; Leivo, Ilmo (Elsevier, 01.04.2020)
      article
      Background The proper estimate of the risk of recurrences in early-stage oral tongue squamous cell carcinoma (OTSCC) is mandatory for individual treatment-decision making. However, this remains a challenge even for ...
    • Design and Implementation of a Wireless Automation Module for Diesel Engines 

      Siemuri, Akpojoto; Glocker, Tobias; Mekkanen, Mike; Kauhaniemi, Kimmo; Mantere, Timo; Rösgren, Jonatan; Kuusisto, Jari; Elmusrati, Mohammed (IEEE, 30.01.2020)
      article
      This paper describes the design of wireless CAN protocol with the aim to replace existing wired CAN protocol communication between the Smart NOx sensor on diesel engines and the Engine Control Unit (ECU). Wireless industrial ...
    • Framework for Random Power Allocation of Wireless Sensor Networks in Fading Channels 

      Elmusrati, Mohammed; Tarhuni, Naser; Jäntti, Riku (Scientific Research Pub., 2012)
      article
      In naturally deaf wireless sensor networks or generally when there is no feedback channel, the fixed-level transmit power of all nodes is the conventional and practical power allocation method. Using random power allocation ...
    • Implementation of an intelligent caravan monitoring system using a simple serial communication protocol for microcontrollers (SSCPM) 

      Glocker, Tobias; Mantere, Timo (Institute of Electrical and Electronics Engineers (IEEE), 2019)
      conferenceObject
      Safety applications play an essential role in our daily life. Without them many accidents would have happened. Especially nowadays, where the amount of traffic increases year by year, safety applications have become an ...
    • Localization services for online common operational picture and situation awareness 

      Björkbom, Mikael; Timonen, Jussi; Yigitler, Huseyin; Kaltiokallio, Ossi; Vallet, Jose M. Garcia; Myrsky, Matthieu; Saarinen, Jari; Korkalainen, Marko; Cuhac, Caner; Koivo, Heikki N.; Jäntti, Riku; Virrankoski, Reino; Vankka, Jouko (IEEE, 25.10.2013)
      article
      Many operations, be they military, police, rescue, or other field operations, require localization services and online situation awareness to make them effective. Questions such as how many people are inside a building and ...
    • Machine learning and wearable devices for Phonocardiogram-based diagnosis 

      Abdelmageed, Shaima; Elmusrati, Mohammed; Meghanathan, Natarajan; Nagamalai, Dhinaharan (AIRCC, 2019)
      article
      The heart sound signal, Phonocardiogram (PCG) is difficult to interpret even for experienced cardiologists. Interpretation are very subjective depending on the hearing ability of the physician. mHealth has been the adopted ...
    • Machine learning application for prediction of locoregional recurrences in early oral tongue cancer: a web-based prognostic tool 

      Alabi, Rasheed Omobolaji; Elmusrati, Mohammed; Sawazaki-Calone, Iris; Kowalski, Luiz Paulo; Haglund, Caj; Coletta, Ricardo D.; Mäkitie, Antti A.; Salo, Tuula; Leivo, Ilmo; Almangush, Alhadi (Springer, 17.08.2019)
      article
      Estimation of risk of recurrence in early-stage oral tongue squamous cell carcinoma (OTSCC) remains a challenge in the field of head and neck oncology. We examined the use of artificial neural networks (ANNs) to predict ...
    • Machine learning in oral squamous cell carcinoma : current status, clinical concerns and prospects for future - A systematic review 

      Alabi, Rasheed Omobolaji; Youssef, Omar; Pirinen, Matti; Elmusrati, Mohammed; Mäkitie, Antti A.; Leivo, Ilmo; Almangush, Alhadi (Elsevier, 01.05.2021)
      article
      Background Oral cancer can show heterogenous patterns of behavior. For proper and effective management of oral cancer, early diagnosis and accurate prediction of prognosis are important. To achieve this, artificial ...
    • Phonocardiogram-based diagnosis using machine learning : parametric estimation with multivariant classification 

      Abdelmageed, Shaima; Elmusrati, Mohammed (AIRCC Publishing Corporation, 2018)
      article
      The heart sound signal, Phonocardiogram (PCG) is difficult to interpret even for experienced cardiologists. Interpretation are very subjective depending on the hearing ability of the physician. mHealth has been the adopted ...
    • Regression Training using Model Parallelism in a Distributed Cloud 

      Reijonen, Joel; Opsenica, Miljenko; Morabito, Roberto; Komu, Miika; Elmusrati, Mohammed; O'Conner, Lisa (IEEE, 04.11.2019)
      article
      Machine learning requires a relevant amount of computational resources and it is usually executed in high-capacity centralized cloud infrastructures (e.g., data centers). In such infrastructures, resources are shared in a ...
    • Secure communication and VoIP threats in next generation networks 

      Hossein Ahmadzadegan, M.; Elmusrati, M.; Mohammadi, H. (World Academy of Science, Engineering and Technology (WASET), 09 / 2013)
      article
      VoIP services are among key issues in the Next Generation Network (NGN) for the telecommunication domain. This technology is comprised of positive and negative aspects like similar emerging technologies. ...
    • Spatial Modulation or Spatial Multiplexing for mmWave Communications? 

      Elkawafi, Salma; Younis, Abdelhamid; Mesleh, Raed; Abouda, Abdulla; Elbarsha, Ahmed; Elmusrati, Mohammed; Sucasas, Victor; Mantas, Georgios; Althunibat, Dr. Saud (Springer, 01 / 2019)
      article
      In this paper, two large scale (LS)–multiple–input multiple–output (MIMO) systems and their performance over 3D statistical outdoor millimeter wave (mmWave) channel model are considered and thoroughly analyzed. Namely, ...
    • Temperature measurements on a solar and low enthalpy geothermal open-air asphalt surface platform in a cold climate region 

      Çuhac, Caner; Mäkiranta, Anne; Välisuo, Petri; Hiltunen, Erkki; Elmusrati, Mohammed (MDPI, 21.02.2020)
      article
      Solar heat, already captured by vast asphalt fields in urban areas, is potentially a huge energy resource. The vertical soil temperature profile, i.e., low enthalpy geothermal energy, reveals how efficiently the irradiation ...