The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria.  Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core.  Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um

على الرغم من التقدم العلمي والتكنولوجي للمعلومات فما زالت الذاكرة تقوم بالدور الاساس بغض النظر عن الامكانيات العلمية في العصر الحديث من حيث ان الكثير من مفرادات الثقافة الانسانية ينقل من جيل الى اخر بواستطتها, ومن الصعب تصور حياة نفسية مقصورة على الحافز فقط, اننا لو اقتصرنا على الحافز لكان التفكير غير ممكن لان الذاكرة هي التي تصل الحافز بالماضي وابسط صورها هي الذاكرة الاولية . فلولا الذاكرة لما تكونت ال

For a long time, the intensification of profit represented a major goal for the company management ,but this goal confirmed a series of restrictions such the constriction on short period, the time rather than on long and medium strategic goal, the relationships with customers ,the supplies, employees , This goal is replaced by another one (intensification of the company's value) ,and the fortune of the share holders itself ,for the purpose  of creating value, the company must generate  great outcomes to cover the operating expense and to insure the a suitable compensation to the invested capital (the market value added) is  the indication used to estimate the company ability to create value –added the development

Abstract:

                This research aims to identify the actual reality of the supply chain processes applied in the Noor Al-Kafeel Food Products Company, which was chosen as a research sample by measuring the application and documentation gap. The current research relies on the case study method to reach the desired results, and the seven-scale scale was relied on to identify the reality of the supply chain operations applied in the researched company and the use of quantitative and qualitative methods in data collection and analysis, as quantitative methods such as the arithmetic mean were used weighted, percentage measurement, and g

Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

In this paper, a procedure to establish the different performance measures in terms of crisp value is proposed for two classes of arrivals and multiple channel queueing models, where both arrival and service rate are fuzzy numbers. The main idea is to convert the arrival rates and service rates under fuzzy queues into crisp queues by using graded mean integration approach, which can be represented as median rule number. Hence, we apply the crisp values obtained to establish the performance measure of conventional multiple queueing models. This procedure has shown its effectiveness when incorporated with many types of membership functions in solving queuing problems. Two numerical illustrations are presented to determine the validity of the