Passive optical network (PON) is a point to multipoint, bidirectional, high rate optical network for data communication. Different standards of PONs are being implemented, first of all PON was ATM PON (APON) which evolved in Broadband PON (BPON). The two major types are Ethernet PON (EPON) and Gigabit passive optical network (GPON). PON with these different standards is called xPON. To have an efficient performance for the last two standards of PON, some important issues will considered. In our work we will integrate a network with different queuing models such M/M/1 and M/M/m model. After analyzing IPACT as a DBA scheme for this integrated network, we modulate cycle time, traffic load, throughput, utilization and overall delay mathematically for single OLT and multiOLT EPON system, and average delay and throughput for single OLT GPON system. A comparison of average delay and throughput between EPON and GPON is introduced with the same number of ONUs. The results show that the proposed multi-OLT EPON system can supports existing bandwidth allocation schemes with better performance than the single-OLT EPON. Cycle delay and average delay is decreased with multi-OLT system than in single OLT system, while throughput of multi-OLT system is higher than throughput of single OLT system. Splitting ratio and throughput in GPON is much higher than in EPON.
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of
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It is no secret to anyone the lofty classifications and wonderful investigations made by Muslim scholars in various eras, with which they removed the dust of ignorance from the nation, clarified the argument, and illuminated the path of education, especially in the legal sciences, which are the foundation of religion.
It is the life of hearts and the path of grammarians in this world and the hereafter.
Among those scientific classifications are the investigations they have written in the science of the principles of legislation, which have established the general evidence and the original rules to which practical legal rulings are referred. And as you know, it is the basis of Islamic jurisprudence, a means of knowing its
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A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the
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A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others
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The Fourth Industrial Revolution represents an advanced stage of technological development, characterized by the integration of digital, physical, and biological technologies, with a strong focus on smart connectivity and advanced data analysis. At the core of this revolution stands Artificial Intelligence (AI), which enables the processing of vast amounts of data, decision-making with speed and accuracy, automation of processes, and enhancement of productivity and quality. This research examines the transformative role of AI in the humanities, particularly in archaeological, historical, and geographical studies, where traditional methods face limitations in handling complex and extensive datasets.The study aims to highlight these l
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The Fourth Industrial Revolution represents an advanced stage of technological development, characterized by the integration of digital, physical, and biological technologies, with a strong focus on smart connectivity and advanced data analysis. At the core of this revolution stands Artificial Intelligence (AI), which enables the processing of vast amounts of data, decision-making with speed and accuracy, automation of processes, and enhancement of productivity and quality. This research examines the transformative role of AI in the humanities, particularly in archaeological, historical, and geographical studies, where traditional methods face limitations in handling complex and extensive datasets.The study aims to highlight these l
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The efficiency of management is determining factor for the success or failure of agricultural projects generally and Livestock particularly achieving its objectives. Therefore, this research came to diagnose the most important variables that determine the efficiency of management using the probability regression models to measure the probability of management efficient of broilers production projects using random sample included (60) broilers projects represented 11.6% of Baghdad province (research community) in 2016. After estimating the relationship between the management efficiency (descriptive dependent variable) and the independent variables affecting it (age, educational level, production index (PI), experience). The results
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