This paper concerned with estimation reliability (­ for K components parallel system of the stress-strength model with non-identical components which is subjected to a common stress, when the stress and strength follow the Generalized Exponential Distribution (GED) with unknown shape parameter α and the known scale parameter θ (θ=1) to be common. Different shrinkage estimation methods will be considered to estimate ­ depending on maximum likelihood estimator and prior estimates based on simulation using mean squared error (MSE) criteria. The study approved that the shrinkage estimation using shrinkage weight function was the best.

تنفذ أجهزة اإلحصاء الدولية ومنها الجهاز المركزي لإلحصاء في العراقإحدى أجهزة وزارة التخطيط، تقوم بإجراء مسوح سنوية ودورية لإنتاج مؤشرات تقييم وتقويم أنشطة القطاعات الاقتصادية المختلفة. يتيح هذا الكم الهائل من البيانات بشكل سلسل زمني لهذه الأجهزة إنتاج مؤشرات جديدة، بما في ذلك القيم التنبؤية لمؤشرات رئيسية تستخدم في إعداد الخطط طويلة وقصيرة المدى. في عام 2015، قامت مديرية الإحصاء الزراعي في الجهاز المركزي للإ

       The implicit is the narrative technique used to give indirect hidden messages. To read between the lines means to understand the implicit meaning that is not directly indicated. This technique is expressed in two forms: the hypothesis and the implications of linguistic and non-linguistic rules. Nathalie Sarraute’s "Pour un oui ou pour un non" states this narrative method through her character’s verbal and non-verbal dialogue. The present paper discusses the implicit method and shows the reason behind which  the author uses it in her play "Pour un oui ou pour un non".

Résumé

The work in this paper involves the planning, design and implementation of a mobile learning system called Nahrain Mobile Learning System (NMLS). This system provides complete teaching resources, which can be accessed by the students, instructors and administrators through the mobile phones. It presents a viable alternative to Electronic learning. It focuses on the mobility and flexibility of the learning practice, and emphasizes the interaction between the learner and learning content. System users are categorized into three categories: administrators, instructors and students. Different learning activities can be carried out throughout the system, offering necessary communication tools to allow the users to communicate with each other

ABSTRACT:. The Lower Cretaceous Zubair formation is comprised of sandstones intercalated with shale sequences. The main challenges that were encountered while drilling into this formation included severe wellbore instability-related issues across the weaker formations overlaying the reservoir section (pay zone). These issues have a significant impact on well costs and timeline. In this paper, a comprehensive geomechanical study was carried out to understand the causes of the wellbore failure and to improve drilling design and drilling performance on further development wells in the field. Failure criteria known as Mogi-Coulomb was used to determine an operating mud weight window required for safe drilling. The accuracy of the geomechanical

The study aimed to examine the impact of audit committee characteristics on the practices of intellectual capital disclosure in the annual reports of Bank and Insurance companies listed on Palestine Exchange, through performing content analysis of the annual reports for the study sample which totaled thirteen companies, including six banks and seven insurance companies. To achieve the study objectives, the study employed a content analysis approach in order to analyze the content of the intellectual capital disclosure practice, in addition, the study used cross-sectional with longitudinal data for time series for a period of time between 2014-2019. The empirical results indicated that financial expertise and the number of meeting

     Automated medical diagnosis is an important topic, especially in detection and classification of diseases. Malaria is one of the most widespread diseases, with more than 200 million cases, according to the 2016 WHO report. Malaria is usually diagnosed using thin and thick blood smears under a microscope. However, proper diagnosis is difficult, especially in poor countries where the disease is most widespread. Therefore, automatic diagnostics helps in identifying the disease through images of red blood cells, with the use of machine learning techniques and digital image processing. This paper presents an accurate model using a Deep Convolutional Neural Network build from scratch. The paper also proposed three CNN

     Agriculture improvement is a national economic issue that extremely depends on productivity. The explanation of disease detection in plants plays a significant role in the agriculture field. Accurate prediction of the plant disease can help treat the leaf as early as possible, which controls the economic loss. This paper aims to use the Image processing techniques with Convolutional Neural Network (CNN). It is one of the deep learning techniques to classify and detect plant leaf diseases. A publicly available Plant village dataset was used, which consists of 15 classes, including 12 diseases classes and 3 healthy classes.  The data augmentation techniques have been used. In addition to dropout and weight reg

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

     A global pandemic has emerged as a result of the widespread coronavirus disease (COVID-19). Deep learning (DL) techniques are used to diagnose COVID-19 based on many chest X-ray. Due to the scarcity of available X-ray images, the performance of DL for COVID-19 detection is lagging, underdeveloped, and suffering from overfitting. Overfitting happens when a network trains a function with an  incredibly high variance to represent the training data perfectly. Consequently, medical images lack the availability of large labeled datasets, and the annotation of medical images is expensive and time-consuming for experts. As the COVID-19 virus is an infectious disease, these datasets are scarce, and it is difficult to get large datasets