The synchronization of a complex network with optoelectronic feedback has been introduced theoretically, with use of 2×2 oscillators network; each oscillator considered is an optocoupler (LED coupled with photo-detector). Fixing the bias current (δ) and increasing the feedback strength (Ԑ) of each oscillator, the dynamical sequence like chaotic and periodic mixed mode oscillations has been observed. Synchronization of unidirectionally coupled of light emitting diodes network has been featured when coupling strength equal to 1.7×10-4. The transition between non-synchronization and synchronization states by means of the spatio-temporal distribution has been investigated.
يعد بيان التدفق النقدي من البيانات المهمة الصادرة من الوحدات الحكومية غير الهادفة للربح، بعد تبنيها معايير IPSASs ، مما يوفر معلومات اوسع تلبي حاجات المستخدمين لأتخاذ القرارات المناسبة . أذ يتضمن بيان التدفق النقدي بموجب المعيار رقم ( 2 ) التدفقات النقدية حسب الأنشطة التشغيلية و الاستثمارية والتمويلية ، وهذا لا ينسجم مع مخرجات النظام المحاسبي الحكومي العراقي . وان هدف البحث هو التعرف
... Show MoreDespite efforts to contain and manage the SARS-CoV-2 outbreak which was declared a public health emergency of international concern in January 2020 by the World Health Organization (WHO), the COVID-19 pandemic still remains a major global challenge. Patients who display the classical symptoms of the infection are easily identified, tested, isolated and monitored. However, many cases of infected asymptomatic patients have been documented. These patients are not easily identified even though many evidences suggest that they can spread the virus to others. How and why these COVID-19 asymptomatic presentations occur remain unclear. The many theories and views are conjectural, and supporting evidences are still needed. In this review, we
... Show MoreObjectives: Dickkopf-1 (DKK-1) is WNT/b-catenin pathway antagonist which plays a detrimental role in the development of diabetic retinopathy (DR). This research aimed to assess serum DKK-1 levels in diabetic patients who have and have not developed DR and, compare them with the control subjects finding out whether we can use it as an indicator for DR early diagnosis and to find out which one of the widely used two groups of antidiabetic treatments had the greater effect on this biomarker and hence on the progression of DR. Methods: The study participants were divided into two subgroups: First, 70 patients (36 male, 34 female) with type 2 diabetes mellitus, among them 35 patients diagnosed with DR and 35 with no evidence of DR, and s
... Show MoreComputer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi
... Show MoreThe major objective of this study is to establish a network of Ground Control Points-GCPs which can use it as a reference for any engineering project. Total Station (type: Nikon Nivo 5.C), Optical Level and Garmin Navigator GPS were used to perform traversing. Traversing measurement was achieved by using nine points covered the selected area irregularly. Near Civil Engineering Department at Baghdad University Al-jadiriya, an attempt has been made to assess the accuracy of GPS by comparing the data obtained from the Total Station. The average error of this method is 3.326 m with the highest coefficient of determination (R2) is 0.077 m observed in Northing. While in
In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.
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