Selaus Oppiaineen mukaanArtikkelitTietoliikennetekniikka

    • Emerging Technologies based Use Case Development for Condition Monitoring and Predictive Maintenance of MV Cables 

      Kumar, Haresh; Kauhaniemi, Kimmo; Elmusrati, Mohammed; Shafiq, Muhammad (IEEE, 28.11.2023)
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      Condition monitoring (CM) and predictive maintenance (PM) techniques can provide a system to achieve a high quality of service with minimal maintenance costs. Using CM -based data, repairing assets is possible based on ...
    • Emerging Wireless Technologies for Reliable Indoor Navigation in Industrial Environments 

      Elsanhoury, Mahmoud; Siemuri, Akpojoto; Nieminen, Jyri; Välisuo, Petri; Koljonen, Janne; Kuusniemi, Heidi; Elmusrati, Mohammed (Institute of Navigation, 09 / 2023)
      article
      Reliable positioning systems are key drivers for location-based services in smart logistics and internet of things (IoT) applications amid the era of Industry 4.0. They are the foundation blocks upon which navigation ...
    • Enhancing the operation of smart inverters with PMU and data concentrators 

      Gargoom, Ameen; Elmusrati, Mohammed; Gaouda, Ahmed (Elsevier, 21.03.2022)
      article
      As inverter-based distributed energy resources (DERs) continue to proliferate in the distribution systems and provide a significant part of the generation, enhancing the visibility of the system for coupling transmission ...
    • Evaluation of Optimization Algorithms for Customers Load Schedule 

      Diaba, Sayawu Yakubu; Elmusrati, Mohammed; Shafie-khah, Miadreza; Ao, S. I.; Castillo, Oscar; Douglas, Craig; Feng, David Dagan (International Association of Engineers (IAENG)Newswood Limited, 2021)
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      This paper introduces a novel concept for customer load scheduling in the Smart Grid (SG). The concept is based on the forthcoming internet of things (IoT). Approximate optimization algorithms are deduced for optimum ...
    • Forecasting Crude Oil Prices using a Hybrid Model Combining Long Short-Term Memory Neural Networks and Markov Switching Model 

      Shahbazbegian, Vahid; Hosseininesaz, Hamid; Shafie-Khah, Miadreza; Elmusrati, Mohammed (IEEE, 19.07.2023)
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      Given the significant impact of crude oil prices on the global economy, accurately predicting their fluctuations is essential for effective decision-making in the energy sector. Therefore, this research aims to develop a ...
    • 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)
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      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 ...
    • Improving Precision GNSS Positioning and Navigation Accuracy on Smartphones using Machine Learning 

      Siemuri, Akpojoto; Selvan, Kannan; Kuusniemi, Heidi; Välisuo, Petri; Elmusrati, Mohammed S. (The Institute of Navigation, 2021)
      article
      In this work, we developed a precision positioning algorithm for multi-constellation dual-frequency global navigation satellite systems (GNSS) receivers that predicts the latitude and longitude from smartphone GNSS data. ...
    • Indoor Asset Tracking in Dense Industrial Environments Using Low-cost Wireless Technologies 

      Elsanhoury, Mahmoud; Nieminen, Jyri; Välisuo, Petri; Siemuri, Akpojoto; Koljonen, Janne; Elmusrati, Mohammed; Kuusniemi, Heidi; Ometov, Aleksandr; Nurmi, Jari; Lohan, Elena Simona; Torres-Sospedra, Joaquín; Kuusniemi, Heidi (R. Piskac c/o Redaktion Sun SITE, Informatik V, RWTH Aachen, 07.07.2023)
      article
      Location based services are becoming abundant and more reliable in today’s world thanks to the technological advancements achieved in the fields of positioning, navigation, and timing. Indoor asset tracking is an essential ...
    • 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 explainability in nasopharyngeal cancer survival using LIME and SHAP 

      Alabi, Rasheed Omobolaji; Elmusrati, Mohammed; Leivo, Ilmo; Almangush, Alhadi; Mäkitie, Antti A. (Springer Nature, 02.06.2023)
      article
      Nasopharyngeal cancer (NPC) has a unique histopathology compared with other head and neck cancers. Individual NPC patients may attain different outcomes. This study aims to build a prognostic system by combining a highly ...
    • 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 ...
    • Managing Cachexia in Head and Neck Cancer : a Systematic Scoping Review 

      Mäkitie, Antti A.; Alabi, Rasheed Omobolaji; Orell, Helena; Youssef, Omar; Almangush, Alhadi; Homma, Akihiro; Takes, Robert P.; López, Fernando; de Bree, Remco; Rodrigo, Juan P.; Ferlito, Alfio (Springer, 27.02.2022)
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      Introduction Patients with head and neck cancer (HNC) are usually confronted with functional changes due to the malignancy itself or its treatment. These factors typically affect important structures involved in speech, ...
    • Measuring the Usability and Quality of Explanations of a Machine Learning Web-Based Tool for Oral Tongue Cancer Prognostication 

      Alabi, Rasheed Omobolaji; Almangush, Alhadi; Elmusrati, Mohammed; Leivo, Ilmo; Mäkitie, Antti (MDPI, 08.07.2022)
      article
      Background: Machine learning models have been reported to assist in the proper management of cancer through accurate prognostication. Integrating such models as a web-based prognostic tool or calculator may help to improve ...
    • Minimizing Collision of Fading Channel Using Machine Learning 

      Alhaddad, Mohaned H.; Sati, Salem; Elmusrati, Mohammed (IEEE, 23.11.2021)
      article
      Energy consumption is considered the main challenge of MAC protocol design. Especially when MAC protocol is employed in an environment of limited energy resources as a wireless sensor network. Parameters optimization of ...
    • Mitigating Burnout in an Oncological Unit : A Scoping Review 

      Alabi, Rasheed Omobolaji; Hietanen, Päivi; Elmusrati, Mohammed; Youssef, Omar; Almangush, Alhadi; Mäkitie, Antti A. (Frontiers Media, 01.10.2021)
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      Objectives: The purpose of this study was to provide a scoping review on how to address and mitigate burnout in the profession of clinical oncology. Also, it examines how artificial intelligence (AI) can mitigate burnout ...
    • On the performance metrics for cyber-physical attack detection in smart grid 

      Diaba, Sayawu Yakubu; Shafie-khah, Miadreza; Elmusrati, Mohammed (Springer, 21.01.2022)
      article
      Supervisory Control and Data Acquisition (SCADA) systems play an important role in Smart Grid. Though the rapid evolution provides numerous advantages it is one of the most desired targets for malicious attackers. So far ...
    • 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 ...