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  1. Article ; Online: Frequency-domain reconfigurable antenna for COVID-19 tracking.

    Akinola, Ayokunle / Singh, Ghanshyam / Ndjiongue, Alain

    Sensors international

    2021  Volume 2, Page(s) 100094

    Abstract: The COVID -19 outbreak since inception has put the whole world in an unprecedented difficult situation by bringing life around the world to a frightening halt and claiming thousands of lives. Due to COVID-19's spreading across 212 countries globally, an ... ...

    Abstract The COVID -19 outbreak since inception has put the whole world in an unprecedented difficult situation by bringing life around the world to a frightening halt and claiming thousands of lives. Due to COVID-19's spreading across 212 countries globally, an increasing number of infected cases and death tolls rose to 146,841,882, and 3,104,743 (as of April 26, 2021), this remains a real threat to the public health system. This paper presents a novel design for the frequency-domain reconfigurable antenna at Ku and K-bands for satellite-internet of thing (IoT) tracking applications. Four reconfigurable antenna is proposed with the use of four different switch mechanisms. Furthermore, switches are used to change resonance frequency to Ku- and K-bands on the antenna surface with four stages. With the help of the 3D electromagnetic computer simulation technology (CST) studio suite, we model the proposed antenna, perform the simulation with a frequency-domain solver, and validate the results with a time-domain solver with both results obtained in agreement as the proposed reconfigurable antenna operates over a wide frequency range for the satellite-IoT network to track COVID-19 pandemic.
    Language English
    Publishing date 2021-04-19
    Publishing country Netherlands
    Document type Journal Article
    ISSN 2666-3511
    ISSN (online) 2666-3511
    DOI 10.1016/j.sintl.2021.100094
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Recurrent Adaptive Classifier Ensemble for Handling Recurring Concept Drifts

    Tinofirei Museba / Fulufhelo Nelwamondo / Khmaies Ouahada / Ayokunle Akinola

    Applied Computational Intelligence and Soft Computing, Vol

    2021  Volume 2021

    Abstract: For most real-world data streams, the concept about which data is obtained may shift from time to time, a phenomenon known as concept drift. For most real-world applications such as nonstationary time-series data, concept drift often occurs in a cyclic ... ...

    Abstract For most real-world data streams, the concept about which data is obtained may shift from time to time, a phenomenon known as concept drift. For most real-world applications such as nonstationary time-series data, concept drift often occurs in a cyclic fashion, and previously seen concepts will reappear, which supports a unique kind of concept drift known as recurring concepts. A cyclically drifting concept exhibits a tendency to return to previously visited states. Existing machine learning algorithms handle recurring concepts by retraining a learning model if concept is detected, leading to the loss of information if the concept was well learned by the learning model, and the concept will recur again in the next learning phase. A common remedy for most machine learning algorithms is to retain and reuse previously learned models, but the process is time-consuming and computationally prohibitive in nonstationary environments to appropriately select any optimal ensemble classifier capable of accurately adapting to recurring concepts. To learn streaming data, fast and accurate machine learning algorithms are needed for time-dependent applications. Most of the existing algorithms designed to handle concept drift do not take into account the presence of recurring concept drift. To accurately and efficiently handle recurring concepts with minimum computational overheads, we propose a novel and evolving ensemble method called Recurrent Adaptive Classifier Ensemble (RACE). The algorithm preserves an archive of previously learned models that are diverse and always trains both new and existing classifiers. The empirical experiments conducted on synthetic and real-world data stream benchmarks show that RACE significantly adapts to recurring concepts more accurately than some state-of-the-art ensemble classifiers based on classifier reuse.
    Keywords Electronic computers. Computer science ; QA75.5-76.95
    Subject code 006
    Language English
    Publishing date 2021-01-01T00:00:00Z
    Publisher Hindawi Limited
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: FSS superstrate antenna for satellite cynosure on IoT to combat COVID-19 pandemic.

    Akinola, Ayokunle / Singh, Ghanshyam / Hashimu, Iddi / Prabhat, Thakur / Nissanov, Uri

    Sensors international

    2021  Volume 2, Page(s) 100090

    Abstract: The global pandemic, COVID-19 needs joint techniques and technology to combat it. The internet of things (IoT) has been at the forefront in solving problems, not only in the health care sector but in other sectors. It delivers accuracy with robustness in ...

    Abstract The global pandemic, COVID-19 needs joint techniques and technology to combat it. The internet of things (IoT) has been at the forefront in solving problems, not only in the health care sector but in other sectors. It delivers accuracy with robustness in the developing service and application. However, it remains clear that the use of IoT is limited to coverage, longevity, security, connectivity issue, immediacy, and multicasting, we proposed in this paper frequency selective surface (FSS) as superstrate for rectangular microstrip antenna. An FSS design combine with the rectangular microstrip antenna for better performance is placed over FSS parallel configuration. The rectangular microstrip antenna was titled 45 degrees to change the band-stop. Analysis of the proposed performance in terms of gain, return loss, and directivity shows that the FSS structure's integration brings better results. With the help of a 3D electromagnetic computer simulation technology CST studio suite, we model the proposed antenna, perform the simulation with a frequency-domain solver, and validate it with a time-domain solver. The proposed impressive result is suitable for satellite networks, which hybrid with IoT can provide a sustainable long-time solution in fighting the COVID-19 pandemic.
    Language English
    Publishing date 2021-03-18
    Publishing country Netherlands
    Document type Journal Article
    ISSN 2666-3511
    ISSN (online) 2666-3511
    DOI 10.1016/j.sintl.2021.100090
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: A decennial cross-sectional review of assisted reproductive technology in a Tertiary Hospital in Southwest Nigeria.

    Ottun, Tawaqualit Abimbola / Adewunmi, Adeniyi Abiodun / Jinadu, Faosat Olayiwola / Olumodeji, Ayokunle Moses / Akinlusi, Fatimat Motunrayo / Rabiu, Kabiru Afolarin / Akinola, Oluwarotimi Ireti / Fabamwo, Adetokunbo Olusegun

    BMC pregnancy and childbirth

    2023  Volume 23, Issue 1, Page(s) 680

    Abstract: Background: The World Health Organization recommends that Assisted Reproductive Technology be complementary to other ethically acceptable solutions to infertility. Whereas fertility centres are increasing in number in urban regions of Africa, published ... ...

    Abstract Background: The World Health Organization recommends that Assisted Reproductive Technology be complementary to other ethically acceptable solutions to infertility. Whereas fertility centres are increasing in number in urban regions of Africa, published reports of their performance are sparse. We present a 10-year review of assisted reproductive technology performed in a public tertiary centre in Lagos, Nigeria.
    Methods: This was a hospital-based, retrospective, cross-sectional review of 604 women, over a 10-year period that had in-vitro fertilization or in-vitro fertilization with intra-cytoplasmic sperm injection at the Institute of Fertility Medicine, Lagos State University Teaching Hospital. Data obtained were expressed in descriptive statistics and Pearson correlation was used to determine the strength of linear relationship between two continuous variables at a significance level of p < 0.05.
    Results: The mean age of the women was of 37.7 ± 6.2 years and 89.7% had no previous parous experience. About 27.2% of the male partners had normal seminal fluid parameters while 4.6% had azoospermia. Median serum follicle stimulating hormone of the women was 8.1 IU/L and median serum anti-mullerian hormone was 6.3 pmol/L. There was weak positive correlation between age and serum follicle stimulating hormone (r = 0.306, p < 0.001); weak negative correlation between age and serum anti-mullerian hormone (r = -0.48, p < 0.001) and very weak correlation between body mass index and serum follicle stimulating hormone (r = 0.173, p = 0.011). In-vitro fertilization and intra-cytoplasmic sperm injection was the method of fertilization used in 97.4% of the cases and 81.8% of embryos formed were of good quality. Most women (94.5%) had 2 embryos transferred and 89.9% had day-5 embryo transfer done. About 1 in 4 of the women (143/604, 23.7%) had clinical pregnancy and 49.7% of women who got pregnant had delivery of a live baby at term while 11.9% had preterm delivery of a live baby.
    Conclusion: Despite increasing use and success of assisted reproductive technology in south-western Nigeria, there is room for improvement in clinical pregnancy rates and live birth rates post- assisted reproductive technology. Complication rates are desirably low.
    MeSH term(s) Infant ; Pregnancy ; Infant, Newborn ; Male ; Female ; Humans ; Adult ; Tertiary Care Centers ; Nigeria ; Anti-Mullerian Hormone ; Cross-Sectional Studies ; Retrospective Studies ; Semen ; Reproductive Techniques, Assisted ; Hospitals, University ; Follicle Stimulating Hormone, Human
    Chemical Substances Anti-Mullerian Hormone (80497-65-0) ; Follicle Stimulating Hormone, Human
    Language English
    Publishing date 2023-09-20
    Publishing country England
    Document type Journal Article
    ZDB-ID 2059869-5
    ISSN 1471-2393 ; 1471-2393
    ISSN (online) 1471-2393
    ISSN 1471-2393
    DOI 10.1186/s12884-023-05964-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

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