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IoT-Based Low-Cost Smart Health Monitoring System using Raspberry Pi Pico W and Blynk Application
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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.

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Publication Date
Sun Aug 01 2021
Journal Name
International Journal Of Electrical And Computer Engineering
Smart element aware gate controller for intelligent wheeled robot navigation
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<p>The directing of a wheeled robot in an unknown moving environment with physical barriers is a difficult proposition. In particular, having an optimal or near-optimal path that avoids obstacles is a major challenge. In this paper, a modified neuro-controller mechanism is proposed for controlling the movement of an indoor mobile robot. The proposed mechanism is based on the design of a modified Elman neural network (MENN) with an effective element aware gate (MEEG) as the neuro-controller. This controller is updated to overcome the rigid and dynamic barriers in the indoor area. The proposed controller is implemented with a mobile robot known as Khepera IV in a practical manner. The practical results demonstrate that the propo

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
The Impact of Agile Methodologies and Cost Management Success Factors: An Empirical Study
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Software cost management is a significant feature of project management. As such, it needs to be employed in a project or line of work. Software cost management is integral to software development failures, which, in turn, cause software failure. Thus, it is imperative that software development professionals develop their cost management skills to deliver successful software projects. The aim of this study is to examine the impact of cost management success factors with project management factors and three agile methodologies – Extreme Programming (XP), Scrum and Kanban methodologies which are used in the Pakistani software industry. To determine the results, the researchers applied quantitative approach through an extensive survey on

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Artificial Neural Network Models to Predict the Cost and Time of Wastewater Projects
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Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

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Publication Date
Sun Jan 01 2017
Journal Name
Lecture Notes In Computer Science
Constrained Differential Evolution for Cost and Energy Efficiency Optimization in 5G Wireless Networks
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The majority of real-world problems involve not only finding the optimal solution, but also this solution must satisfy one or more constraints. Differential evolution (DE) algorithm with constraints handling has been proposed to solve one of the most fundamental problems in cellular network design. This proposed method has been applied to solve the radio network planning (RNP) in the forthcoming 5G Long Term Evolution (5G LTE) wireless cellular network, that satisfies both deployment cost and energy savings by reducing the number of deployed micro base stations (BSs) in an area of interest. Practically, this has been implemented using constrained strategy that must guarantee good coverage for the users as well. Three differential evolution

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
Bioremediation of Petroleum Hydrocarbons Contaminated Soil using Bio piles System
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This study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity.

Four bacterial strains were isolated from diesel contaminated soil samples. The isolates were identified by the Vitek 2 system, as Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae. The potential of biological surfactant production was tested using the Sigma 703D stand-alone tensiometer showed

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Publication Date
Sun Feb 28 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Intelligent System for Parasitized Malaria Infection Detection Using Local Descriptors
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Malaria is a curative disease, with therapeutics available for patients, such as drugs that can prevent future malaria infections in countries vulnerable to malaria. Though, there is no effective malaria vaccine until now, although it is an interesting research area in medicine. Local descriptors of blood smear image are exploited in this paper to solve parasitized malaria infection detection problem. Swarm intelligence is used to separate the red blood cells from the background of the blood slide image in adaptive manner. After that, the effective corner points are detected and localized using Harris corner detection method. Two types of local descriptors are generated from the local regions of the effective corners which are Gabor based f

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Development an Anomaly Network Intrusion Detection System Using Neural Network
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Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

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Publication Date
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
Pose Invariant Palm Vein Identification System using Convolutional Neural Network
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Palm vein recognition is a one of the most efficient biometric technologies, each individual can be identified through its veins unique characteristics, palm vein acquisition techniques is either contact based or contactless based, as the individual's hand contact or not the peg of the palm imaging device, the needs a contactless palm vein system in modern applications rise tow problems, the pose variations (rotation, scaling and translation transformations) since the imaging device cannot aligned correctly with the surface of the palm, and a delay of matching process especially for large systems, trying to solve these problems. This paper proposed a pose invariant identification system for contactless palm vein which include three main

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Publication Date
Wed Feb 01 2017
Journal Name
International Journal Of Science And Research (ijsr)
Supra-Approximation Spaces Using Mixed Degree System in Graph Theory
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This paper is concerned with introducing and studying the o-space by using out degree system (resp. i-space by using in degree system) which are the core concept in this paper. In addition, the m-lower approximations, the m-upper approximations and ospace and i-space. Furthermore, we introduce near supraopen (near supraclosed) d. g.'s. Finally, the supra-lower approximation, supraupper approximation, supra-accuracy are defined and some of its properties are investigated.

Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
Bioremediation of Petroleum Hydrocarbons Contaminated Soil using Bio piles System
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This study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity. Four bacterial strains were isolated from diesel contaminated soil samples. The isolates were identified by the Vitek 2 system, as Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae. The potential of biological surfactant production was tested using the Sigma 703D stand-alone tensiometer showed that these isolates are biological surfactant producers. The bet

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