في السنوات الأخيرة، أدى التقدم التكنولوجي في إنترنت الأشياء (IoT) وأجهزة الاستشعار الذكية إلى فتح اتجاهات جديدة وإعطاء حلول عملية في مختلف قطاعات الحياة. يتم التعرف على إنترنت الأشياء كتنولوجيا حديثة تربط بين مختلف انواع الشبكات. تم تحسين أنواع مختلفة من قطاعات الرعاية الصحية في المجال الطبي بناءً على هذه التكنولوجيا. أحد هذه القطاعات الهامة هو نظام مراقبة الصحة (HMS). تعتبر مراقبة المريض عن بعد لاسلكيًا وبتكلفة منخفضة أمرًا بالغ الأهمية في هذا المجال. في هذا العمل، تم اقتراح نظام مراقبة صحة المريض في الوقت الحقيقي وبتكلفة منخفضة. يتم دمج أنواع مختلفة من أجهزة الاستشعار في شبكة اتصالات لاسلكية لجمع الإشارات الفسيولوجية للمريض عن بعد وإرسالها إلى المختص في أسرع وقت ممكن. يتكون االنظام المقترح من عدد من أجهزة الاستشعار الذكية التي تقيس معلمات مختلفة وهي: عدد نبضات القلب بالدقيقة، درجة حرارة الجسم، وSPO2 (تشبع الأكسجين). تُستخدم هذه الحساسات لحساب معدل ضربات قلب المريض ودرجة حرارة الجسم ونسبة تشبع الأكسجين للمريض على التوالي. يتم عرض حالة المريض اما على شاشة OLED اوباستخدام تطبيق Blynk. في هذا النظام نستخدم لوحة Raspberry Pi Pico W كوحدة تحكم دقيقة مع مفهوم الحوسبة السحابية. بحيث يتم استخدام لوحة Raspberry Pi Pico W لنقل البيانات لاسلكيًا على تقنية إنترنت الأشياء باستخدام تطبيق Blynk. يتم نقل المعلمات الحيوية للمريض عن بعد عبر شبكة Wi-Fi مما يساعد في مراقبة المعلومات الصحية للمرضى لاسلكيًا وفي الوقت الحقيقي. من خلال النتائج التي تم الحصول عليها وجد ان البيانات التي تم الحصول عليها من المريض يتم نقلها بسرعة كبيرة ويمكننا فحص العديد من المرضى عن بعد من خلال الحفاظ على مسافة مناسبة مع المرضى. تم مقارنة النظام المقترح مع الانظمة الموجودة عن طريق قياس العلامات الحيوية لعدد من الأشخاص وأظهرت النتائج أن البيانات التي تم الحصول عليها من الأشخاص متقاربة جدا. علاوة على ذلك، فقد وجد أن النظام المقترح ذو تكلفة منخفضة مقارنة بالأجهزة الأخرى المتوفرة تجاريا.
Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In
... Show MoreBackground: Acute appendicitis is the most common abdominal surgical emergency. The diagnosis of this condition is still essentially clinical and there is difficulty in the clinical diagnosis, especially among elderly, children and patients with a typical presentation, so early and accurate diagnosis of acute appendicitis is important to avoid its complications.Objectives: To evaluate the degree of accuracy of Alvarado scoring system in the diagnosis of acute appendicitis.Method: Two hundred patients were admitted to the Alkindy Teaching Hospital from January 2011 to april 2014- presented with symptoms and signs suggestive of acute appendicitis. After examination and investigations all patients were given a score according to Alvarado sc
... Show MoreFingerprint recognition is one among oldest procedures of identification. An important step in automatic fingerprint matching is to mechanically and dependably extract features. The quality of the input fingerprint image has a major impact on the performance of a feature extraction algorithm. The target of this paper is to present a fingerprint recognition technique that utilizes local features for fingerprint representation and matching. The adopted local features have determined: (i) the energy of Haar wavelet subbands, (ii) the normalized of Haar wavelet subbands. Experiments have been made on three completely different sets of features which are used when partitioning the fingerprint into overlapped blocks. Experiments are conducted on
... Show MoreMedicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea
... Show MoreThis investigation aimed to explain the mechanism of MFCA by applying this method on air-cooled engine factory which was suffering from high production cost. The results of this study revealed that MFCA is a useful tool to identify losses and inefficiencies of the production process. It is found that the factory is suffering from high losses due to material energy and system losses. In conclusion, it is calculated that system losses are the highest among all the losses due to inefficient use of available production capacity.
This study aimed to evaluate oral health (OH) and periodontal diseases (PD) awareness in the Iraqi population.
This study was a questionnaire‐based online survey of two weeks duration. The questionnaire was built using a Google platform and was distributed randomly via social media (Facebook and Telegram). The questionnaire consisted of a demographic data section and two other main sections for the evaluation of OH and PD awareness. Each response was marked with “1” for a positive answer and “0” for the other answers. For each respondent, answers were summed to give
This research is a case study to solve control problems in Al Rasheed edible oil factory fire tube boilers. they have hopes to develop a new control system to manage boilers operation. The suggestion is to use Zelio soft programmable relays instead of the unavailable old control units. Operation philosophy was studied through works of literature, operation manuals, and standards. Programmable logic control relay is proposed as an advanced selection than PLC's. Boilers operation is accompanied by operation risks. many boilers were exploded in Iraq for different reasons. Some problems are attributed to manual operation mistakes. Extensive work was done to understand the operation sequence, emergency shutdown, and faults causing the trips. A c
... Show MoreBack ground: Zygote produce from once a sperm fertilizes an egg cell. Then, the zygote (unicellular) will begin chain of cellular cleavages to produce multicellular mass, its embryo, the differentiated to different tissues and organism. The development of the embryo is called embryogenesis. Coenzyme Q10, is an antioxidant produced in the body. It boosts cellular energy and may enhance the immune system. CoQ10 is present and measurable in seminal fluid, the concentration of CoQ10 directly correlates with both sperm count and motility. It is beneficial in the prevention and treatment a wide range of health problems. Objectives: The present study was aimed to investigate the possibility of using coenzyme Q10 to improve in vitro fertilization (
... Show MoreNon uniform channelization is a crucial task in cognitive radio receivers for obtaining separate channels from the digitized wideband input signal at different intervals of time. The two main requirements in the channelizer are reconfigurability and low complexity. In this paper, a reconfigurable architecture based on a combination of Improved Coefficient Decimation Method (ICDM) and Coefficient Interpolation Method (CIM) is proposed. The proposed Hybrid Coefficient Decimation-Interpolation Method (HCDIM) based filter bank (FB) is able to realize the same number of channels realized using (ICDM) but with a maximum decimation factor divided by the interpolation factor (L), which leads to less deterioration in stop band at
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