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An Automatic Deep Neural Network Model for Fingerprint Classification

Intelligent Automation & Soft Computing 2023年第5期36卷 2007-2023页

作者： amira tarek mahmoud Wael AAwad Gamal Behery Mohamed Abouhawwash Mehedi Masud Hanan Aljuaid Ahmed Ismail Ebada Department of Computer Science Faculty of SciencePort Said UniversityPort SaidEgypt Department of Computer Science Faculty of Computers and Artificial IntelligenceDamietta UniversityNew DamiettaEgypt Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)College of EngineeringMichigan State UniversityEast LansingMI 48824USA Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Computer Sciences Department College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman University(PNU)P.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems Faculty of Computers and Artificial IntelligenceDamietta UniversityNew DamiettaEgypt

The accuracy ofﬁngerprint recognition model is extremely important due to its usage in forensic and securityﬁ***ﬁngerprint recognition system has particular network architecture whereas many other networks achieve higher *** solve this problem in a uniﬁed model,this paper proposes a model that can automatically specify ***,it is called an automatic deep neural net-work(ADNN).Our algorithm can specify the appropriate architecture of the neur-al network used and some signiﬁcant parameters of this *** parameters are the number ofﬁlters,epochs,and *** guarantees the high-est accuracy by updating itself until achieving 99%accuracy then it stops and out-puts the ***,this paper proposes an end-to-end methodology for recognizing a person’s identity from the inputﬁngerprint image based on a resi-dual convolutional neural *** is a complete system and is fully automated whether in the features extraction stage or the classiﬁcation *** goal is to automate thisﬁngerprint recognition system because the more automatic the sys-tem is,the more time and effort it *** model also allows users to react by inputting the initial values of these ***,the model updates itself until itﬁnds the optimal values for the parameters and achieves the best *** advantage of our algorithm is that it can recognize people from their thumb and otherﬁngers and its ability to recognize distorted *** algo-rithm achieved 99.75%accuracy on the publicﬁngerprint dataset(SOCOFing).This is the best accuracy compared with other models.

关键词： Automatic system ﬁngerprint classiﬁcation residual networks deep learning

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The Inhibitory Effect of Curcumin on Ornithine Decarboxylase against Hepatic Carcinoma

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Journal of Biosciences and Medicines 2019年第5期7卷 127-145页

作者： Abeer A. Khamis amira H. Sharshar Amal H. mahmoud tarek M. Mohamed Biochemistry Division Chemistry Department Faculty of Science Tanta University Tanta Egypt Head Researcher of Special Food and Nutrition Department Food Technology Research Institute Agricultural Research Center Giza Egypt

Curcumin the active component of turmeric is widely used as an anticancer agent for treating many human cancers. This study aimed at the extraction of curcumin from Curcuma Longa and investigates its therapeutic effect as ornithine decarboxylase (ODC) inhibitor in HepG2 cells. The proliferation of HepG2 cells was carried out by using the MTT assay. In addition, cell cycle analysis was evaluated by using the flow-cytometric technique. Our results showed that curcumin has the ability to inhibit the proliferation of HepG2 cells with IC50 of 24.79 μg/ml and induced G2/M cell cycle arrest. Moreover, it caused an elevation in the intracellular concentration of Ca2+. Moreover, in the curcumin administration the downregulation expression level of ODC and Bcl-2 genes (p ≤ 0.05) was significant found. On the other hand, upregulation in the expression level of P53, Bax, and caspase-3 genes (p ≤ 0.05). This study concluded that curcumin may be considered as a new saving candidate for the future progress of antitumor agents.

关键词： Curcumin-HepG2 Cells-Apoptosis Ornithine Decarboxylase Bax Cell Cycle

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Risk-Adapted, Combined-Modality Therapy for Unfavorable Pediatric Hodgkin Lymphom

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Journal of Cancer Therapy 2018年第7期9卷 545-558页

作者： Amany M. Ali amira M. Mohamed Shimaa Ahmed Mohamed Abdallah tarek M. Alsaba Samar Mansour Pediatric Oncology Department South Egypt Cancer Institute Assiut University Assiut Egypt Radiotherapy Department South Egypt Cancer Institute Assiut University Assiut Egypt Radiology Department South Egypt Cancer Institute Assiut University Assiut Egypt Pathology Department South Egypt Cancer Institute Assiut University Assiut Egypt Clinical Pathology Department South Egypt Cancer Institute Assiut University Assiut Egypt

Background and Objectives: Risk-adapted therapy for children with HL is directed toward high survival, minimal toxicity and optimal quality of life, with long term follow up. We assess the impact of prognostic factors associated with local treatment failure of pediatric HL patients with unfavorable criteria treated with combined modality: Alternating ABVD (Doxorubicin, Bleomycin, Vinblastine and Decarbazine) and COEP (Cyclophosphamide, Oncovin, Etoposide and Prednisone) chemotherapy and response-based, involved-field radiation for newly diagnosed unfavorable pediatric HL patients, also will detect toxicities and long-term complications observed in the patients. Methods: This prospective study was carried out from January 2010 to January 2018, with a median follow up of 74 months (range 8 - 103 months). 54 patients were eligible for this study stratified into two groups: intermediate risk (IR) and high-risk group (HR). Patients were treated with (4 - 6 cycles) and (6 - 8 cycles) respectively of alternating ABVD/COEP chemotherapy followed by involved-field radiation therapy (IFRT): 15 Gy for patients achieved complete response, and 25.5 Gy for those achieved a partial response. Results: 27 patients were IR and 27 patients were HR. There were 16 treatment failures;5 patients had progressive disease;and 11 patients had a relapse. 9 patients died from their disease progression. The 5-year overall survival (OS) and event-free survival (EFS) rates (±SE) were 81.8% ± 5.7% and 71.8% ± 6.2% respectively. Multivariate analysis revealed that the only independent factor for inferior OS was radiotherapy. Conclusion: Treatment results of unfavourable HL patients in our study are satisfactory for with IR group but not for HR group who needs intensification of therapy. Radiotherapy is considered as a cornerstone in the treatment of the patients with unfavourable criteria with better assessment of early responders needed by PET-CT to identify patients at risk for relapse.

关键词： Risk-Adapted Combined-Modality Unfavourable Pediatric Hodgkin Lymphoma

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