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  • 1
    Online-Ressource
    Online-Ressource
    Springer Science and Business Media LLC ; 2022
    In:  International Journal of Information Technology Vol. 14, No. 2 ( 2022-03), p. 827-835
    In: International Journal of Information Technology, Springer Science and Business Media LLC, Vol. 14, No. 2 ( 2022-03), p. 827-835
    Materialart: Online-Ressource
    ISSN: 2511-2104 , 2511-2112
    Sprache: Englisch
    Verlag: Springer Science and Business Media LLC
    Publikationsdatum: 2022
    ZDB Id: 2878562-9
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 2
    In: Materials, MDPI AG, Vol. 14, No. 21 ( 2021-10-26), p. 6420-
    Kurzfassung: The mechanical, physical and interfacial properties of aluminum alloys are improved by reinforcing the silicon carbide particles (SiCp). Machinability of such alloys by traditional methods is challenging due to higher tool wear and surface roughness. The objective of research is to investigate the machinability of SiCp reinforced Al6061 composite by Wire-Electrical Discharge Machining (wire-EDM). The effect of wire-EDM parameters namely current (I), pulse-on time (Ton), wire-speed (Ws), voltage (Iv) and pulse-off time (Toff) on material removal rate (MRR) is investigated and their settings are optimized for achieving the high MRR. The experiments are designed by using Taguchi L16 orthogonal arrays. The MRR obtained at different experiments are analyzed using statistical tools. It is observed that all the chosen process parameters showed significant influence of on the MRR with contribution of 27.39%, 22.08%, 21.32%, 15.76% and 12.94% by I, Iv, Toff, Ton and Ws, respectively. At optimum settings, the Wire-EDM resulted in MRR of 65.21 mg/min and 62.41 mg/min for samples with 4% and 8% SiCp. The results also indicated reinforcing SiCp upto 8% showed marginally low influence on MRR. Microstructural investigation of the cut surface revealed the presence of craters with wave pattern on its surface. The top surface of the crater is featured by the recast layers connecting adjacent craters. Further, the statistical model is developed using linear regression to predict the MRR (?2—73.65%) and its predicting accuracy is verified by the confirmation trials. The statistical model is useful for predicting the MRR for different settings of the process parameters. The optimized settings can be used to improve the machining productivity by increasing the MRR while machining of Al6061-SiCp (upto 8 wt. %) alloy by wire-EDM industries.
    Materialart: Online-Ressource
    ISSN: 1996-1944
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2021
    ZDB Id: 2487261-1
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 3
    Online-Ressource
    Online-Ressource
    Springer Science and Business Media LLC ; 2019
    In:  Wireless Personal Communications Vol. 106, No. 2 ( 2019-5), p. 275-306
    In: Wireless Personal Communications, Springer Science and Business Media LLC, Vol. 106, No. 2 ( 2019-5), p. 275-306
    Materialart: Online-Ressource
    ISSN: 0929-6212 , 1572-834X
    Sprache: Englisch
    Verlag: Springer Science and Business Media LLC
    Publikationsdatum: 2019
    ZDB Id: 1479327-1
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 4
    In: Computation, MDPI AG, Vol. 11, No. 3 ( 2023-03-13), p. 59-
    Kurzfassung: Early detection and timely breast cancer treatment improve survival rates and patients’ quality of life. Hence, many computer-assisted techniques based on artificial intelligence are being introduced into the traditional diagnostic workflow. This inclusion of automatic diagnostic systems speeds up diagnosis and helps medical professionals by relieving their work pressure. This study proposes a breast cancer detection framework based on a deep convolutional neural network. To mine useful information about breast cancer through breast histopathology images of the 40× magnification factor that are publicly available, the BreakHis dataset and IDC(Invasive ductal carcinoma) dataset are used. Pre-trained convolutional neural network (CNN) models EfficientNetB0, ResNet50, and Xception are tested for this study. The top layers of these architectures are replaced by custom layers to make the whole architecture specific to the breast cancer detection task. It is seen that the customized Xception model outperformed other frameworks. It gave an accuracy of 93.33% for the 40× zoom images of the BreakHis dataset. The networks are trained using 70% data consisting of BreakHis 40× histopathological images as training data and validated on 30% of the total 40× images as unseen testing and validation data. The histopathology image set is augmented by performing various image transforms. Dropout and batch normalization are used as regularization techniques. Further, the proposed model with enhanced pre-trained Xception CNN is fine-tuned and tested on a part of the IDC dataset. For the IDC dataset training, validation, and testing percentages are kept as 60%, 20%, and 20%, respectively. It obtained an accuracy of 88.08% for the IDC dataset for recognizing invasive ductal carcinoma from H & E-stained histopathological tissue samples of breast tissues. Weights learned during training on the BreakHis dataset are kept the same while training the model on IDC dataset. Thus, this study enhances and customizes functionality of pre-trained model as per the task of classification on the BreakHis and IDC datasets. This study also tries to apply the transfer learning approach for the designed model to another similar classification task.
    Materialart: Online-Ressource
    ISSN: 2079-3197
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2023
    ZDB Id: 2723192-6
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 5
    Online-Ressource
    Online-Ressource
    Elsevier BV ; 2023
    In:  Cleaner Logistics and Supply Chain Vol. 8 ( 2023-09), p. 100115-
    In: Cleaner Logistics and Supply Chain, Elsevier BV, Vol. 8 ( 2023-09), p. 100115-
    Materialart: Online-Ressource
    ISSN: 2772-3909
    Sprache: Englisch
    Verlag: Elsevier BV
    Publikationsdatum: 2023
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 6
    Online-Ressource
    Online-Ressource
    Institute of Electrical and Electronics Engineers (IEEE) ; 2021
    In:  IEEE Access Vol. 9 ( 2021), p. 158367-158401
    In: IEEE Access, Institute of Electrical and Electronics Engineers (IEEE), Vol. 9 ( 2021), p. 158367-158401
    Materialart: Online-Ressource
    ISSN: 2169-3536
    Sprache: Unbekannt
    Verlag: Institute of Electrical and Electronics Engineers (IEEE)
    Publikationsdatum: 2021
    ZDB Id: 2687964-5
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 7
    In: International Journal of Financial Studies, MDPI AG, Vol. 11, No. 3 ( 2023-07-26), p. 94-
    Kurzfassung: The financial sector has greatly impacted the monetary well-being of consumers, traders, and financial institutions. In the current era, artificial intelligence is redefining the limits of the financial markets based on state-of-the-art machine learning and deep learning algorithms. There is extensive use of these techniques in financial instrument price prediction, market trend analysis, establishing investment opportunities, portfolio optimization, etc. Investors and traders are using machine learning and deep learning models for forecasting financial instrument movements. With the widespread adoption of AI in finance, it is imperative to summarize the recent machine learning and deep learning models, which motivated us to present this comprehensive review of the practical applications of machine learning in the financial industry. This article examines algorithms such as supervised and unsupervised machine learning algorithms, ensemble algorithms, time series analysis algorithms, and deep learning algorithms for stock price prediction and solving classification problems. The contributions of this review article are as follows: (a) it provides a description of machine learning and deep learning models used in the financial sector; (b) it provides a generic framework for stock price prediction and classification; and (c) it implements an ensemble model—“Random Forest + XG-Boost + LSTM”—for forecasting TAINIWALCHM and AGROPHOS stock prices and performs a comparative analysis with popular machine learning and deep learning models.
    Materialart: Online-Ressource
    ISSN: 2227-7072
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2023
    ZDB Id: 2704235-2
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 8
    Online-Ressource
    Online-Ressource
    International Information and Engineering Technology Association ; 2024
    In:  Revue d'Intelligence Artificielle Vol. 38, No. 3 ( 2024-6-21), p. 847-855
    In: Revue d'Intelligence Artificielle, International Information and Engineering Technology Association, Vol. 38, No. 3 ( 2024-6-21), p. 847-855
    Materialart: Online-Ressource
    ISSN: 0992-499X , 1958-5748
    URL: Issue
    Sprache: Unbekannt
    Verlag: International Information and Engineering Technology Association
    Publikationsdatum: 2024
    ZDB Id: 2391409-9
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 9
    In: Life, MDPI AG, Vol. 13, No. 9 ( 2023-08-23), p. 1794-
    Kurzfassung: Umbilical cord blood (UCB) is a rich source of hematopoietic cells that can be used to replace bone marrow components. Many blood disorders and systemic illnesses are increasingly being treated with stem cells as regenerative medical therapy. Presently, collected blood has been stored in either public or private banks for allogenic or autologous transplantation. Using a specific keyword, we used the English language to search for relevant articles in SCOPUS and PubMed databases over time frame. According to our review, Asian countries are increasingly using UCB preservation for future use as regenerative medicine, and existing studies indicate that this trend will continue. This recent literature review explains the methodology of UCB collection, banking, and cryopreservation for future clinical use. Between 2010 and 2022, 10,054 UCB stem cell samples were effectively cryopreserved. Furthermore, we have discussed using Mesenchymal Stem Cells (MSCs) as transplant medicine, and its clinical applications. It is essential for healthcare personnel, particularly those working in labor rooms, to comprehend the protocols for collecting, transporting, and storing UCB. This review aims to provide a glimpse of the details about the UCB collection and banking processes, its benefits, and the use of UCB-derived stem cells in clinical practice, as well as the ethical concerns associated with UCB, all of which are important for healthcare professionals, particularly those working in maternity wards; namely, the obstetrician, neonatologist, and anyone involved in perinatal care. This article also highlights the practical and ethical concerns associated with private UCB banks, and the existence of public banks. UCB may continue to grow to assist healthcare teams worldwide in treating various metabolic, hematological, and immunodeficiency disorders.
    Materialart: Online-Ressource
    ISSN: 2075-1729
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2023
    ZDB Id: 2662250-6
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 10
    Online-Ressource
    Online-Ressource
    Inderscience Publishers ; 2019
    In:  International Journal of Communication Networks and Distributed Systems Vol. 23, No. 3 ( 2019), p. 380-
    In: International Journal of Communication Networks and Distributed Systems, Inderscience Publishers, Vol. 23, No. 3 ( 2019), p. 380-
    Materialart: Online-Ressource
    ISSN: 1754-3916 , 1754-3924
    Sprache: Englisch
    Verlag: Inderscience Publishers
    Publikationsdatum: 2019
    Standort Signatur Einschränkungen Verfügbarkeit
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