Low-cost ventilator pressure modes realization and artificial intelligence assisted design / by Ahmed Abdellatif Mohammed Elsaber ; Supervisors Prof. Dr. Mohammed R.ElGhonemi.

By:

Ahmed Abdellatif Mohammed Elsaber [preparation.]

Contributor(s):

Mohamed R.El-Ghonemi [thesis advisor.]

Material type: Text

TextLanguage: English Summary language: English, Arabic Producer: 2024Description: 58 pages : illustrations ; 30 cm. + CDContent type:

text

Media type:

Unmediated

Carrier type:

volume

Other title:

تنفيذ أنماط الضغط لجهاز التنفس الصناعى منخفض التكلفة والتصميم بمساعدة الذكاء الاصطناعي [Added title page title]

Subject(s):

DDC classification:

610.28

Available additional physical forms:

Issues also as CD.

Dissertation note: Thesis (M.Sc)-Cairo University, 2024. Summary: The Corona virus revealed the severe shortage of the medical ventilators around the world. This was the reason behind the trial to find a low-cost solution that uses commercially available components. This thesis presented the design and development of pressure control modes in a low-cost medical ventilator using artificial intelligence assisted design, where the proposed neural network provides better results than others. The results of the medical ventilator were verified using the readings of the biomedical monitoring (FLUKE) device to ensure that the device is functioning properlySummary: قدمت هذه الرسالة تصميم وتطوير أوضاع التحكم في الضغط في جهاز تنفس طبي منخفض التكلفة باستخدام تصميم مدعوم بالذكاء الاصطناعي، حيث توفر الشبكة العصبية المقترحة نتائج أفضل من غيرها. تم التحقق من نتائج جهاز التنفس الصناعي الطبي باستخدام قراءات جهاز المراقبة الطبية الحيوية (فلوك) للتأكد من أن الجهاز يعمل بشكل صحيح.

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Item type	Current library	Home library	Call number	Status	Barcode
Thesis	قاعة الرسائل الجامعية - الدور الاول	المكتبة المركزبة الجديدة - جامعة القاهرة	Cai01.13.08.M.Sc.2024.Ah.L (Browse shelf(Opens below))	Not for loan	01010110090804000

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Previous	Cai01.13.08.M.Sc.2023.Yo.F Fpga-Based Hardware Design Of A Fully-Stochastic Spiking Neural Network /	Cai01.13.08.M.Sc.2024.Ab.S 70-90GHZ mixer-first receiver in 22-NM SOI /	Cai01.13.08.M.Sc.2024.Ah.F A framework for automatic generation of convolutional neural networks efficient hardware accelerators /	Cai01.13.08.M.Sc.2024.Ah.L Low-cost ventilator pressure modes realization and artificial intelligence assisted design /	Cai01.13.08.M.Sc.2024.Es.E. Efficient ASIC Implementation for Satellite-IoT Security /	Cai01.13.08.M.Sc.2024.Is.P Particle swarm optimization of machine learning in cognitive radio E_health network at low SNR /	Cai01.13.08.M.Sc.2024.Mo.E Enhanced single-shot beam-training using true-time-delay units for mmwave hybrid arrays /	Next

Thesis (M.Sc)-Cairo University, 2024.

Bibliography: pages 54-58.

The Corona virus revealed the severe shortage of the medical ventilators around the world. This was the reason behind the trial to find a low-cost solution that uses commercially available components. This thesis presented the design and development of pressure control modes in a low-cost medical ventilator using artificial intelligence assisted design, where the proposed neural network provides better results than others. The results of the medical ventilator were verified using the readings of the biomedical monitoring (FLUKE) device to ensure that the device is functioning properly

قدمت هذه الرسالة تصميم وتطوير أوضاع التحكم في الضغط في جهاز تنفس طبي منخفض التكلفة باستخدام تصميم مدعوم بالذكاء الاصطناعي، حيث توفر الشبكة العصبية المقترحة نتائج أفضل من غيرها. تم التحقق من نتائج جهاز التنفس الصناعي الطبي باستخدام قراءات جهاز المراقبة الطبية الحيوية (فلوك) للتأكد من أن الجهاز يعمل بشكل صحيح.

Issues also as CD.

Text in English and abstract in Arabic & English.

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