The rise of edge-cloud continuum computing is a result of the growing significance of edge computing, which has become a complementary or substitute option for traditional cloud services. The convergence of networking and computers presents a notable challenge due to their distinct historical development. Task scheduling is a major challenge in the context of edge-cloud continuum computing. The selection of the execution location of tasks, is crucial in meeting the quality-of-service (QoS) requirements of applications. An efficient scheduling strategy for distributing workloads among virtual machines in the edge-cloud continuum data center is mandatory to ensure the fulfilment of QoS requirements for both customer and service provider. E

In light of increasing demand for energy consumption due to life complexity and its requirements, which reflected on architecture in type and size, Environmental challenges have emerged in the need to reduce emissions and power consumption within the construction sector. Which urged designers to improve the environmental performance of buildings by adopting new design approaches, Invest digital technology to facilitate design decision-making, in short time, effort and cost. Which doesn’t stop at the limits of acceptable efficiency, but extends to the level of (the highest performance), which doesn’t provide by traditional approaches that adopted by researchers and local institutions in their studies and architectural practices, limit

The impact of undergraduate research experiences on students' academic development and retention in STEM fields is significant. Students' success in STEM fields is based on developing strong research and critical thinking skills that make it essential for students to engage in research activities throughout their academic programs. This work evaluates the effectiveness of undergraduate research experiences with respect to its influence on student retention and academic development. The cases presented are based on years of experience implementing undergraduate research programs in various STEM fields at Colorado State University Pueblo (CSU Pueblo) funded by HSI STEM Grants. The study seeks to establish a correlation between students' reten

This work deals with thermal cracking of heavy vacuum gas oil which produced from the top of vacuum distillation unit at Al- DURA refinery, by continuous process. An experimental laboratory plant scale was constructed in laboratories of chemical engineering department, Al-Nahrain University and Baghdad University. The thermal cracking process was carried out at temperature ranges between 460-560^oC and atmospheric pressure with liquid hourly space velocity (LHSV) equal to 15hr^-1.The liquid product from thermal cracking unit was distilled by atmospheric distillation device according to ASTM D-86 in order to achieve two fractions, below 220^oC as a gasoline fraction and above 220^oC as light cycle o

An experiment was conducted to study how SAE 50 engine oil contaminated with diesel fuel affects engine performance. The engine oil was contaminated with diesel fuel at concentrations of 0%, 1%, and 3%. The following performance characteristics were studied: brake-specific fuel consumption, brake thermal efficiency, friction power, and exhaust gas temperature. Each treatment was tested three times. The three treatments (0%, 1%, and 3%) were analyzed statistically with a one-way ANOVA model at the 5% probability level to determine if the three treatments produced significant differences in engine performance. The statistical results showed that there were significant differences in engine performance metrics among the three treatments. The 3

ناقش البحث في طياته عدداً من القضايا الرئيسة المتعلقة بالتقييم الاستراتيجي والإطار العام للخطة الاستراتيجية المقترحة لشركة نفط ميسان للسنوات الخمس المقبلة (2020_2024)، وهدف هذا البحث يتمحور في تقييم عملية صياغة استراتيجية شركة نفط ميسان لتحديد نقاط القوة وتعضيدها ومواطن الضعف ومحاولة معالجتها لتجنب الوقوع بها عند وضع استراتيجية للسنوات القادمة، وعلى هذا الاساس فان مشكلة البحث تكمن في مدى نجاح الاستراتي

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

The downhole flow profiles of the wells with single production tubes and mixed flow from more than one layer can be complicated, making it challenging to obtain the average pressure of each layer independently.  Production log data can be used to monitor the impacts of pressure depletion over time and to determine average pressure with the use of Selective Inflow Performance (SIP). The SIP technique provides a method of determining the steady state of inflow relationship for each individual layer. The well flows at different stabilized surface rates, and for each rate, a production log is run throughout the producing interval to record both downhole flow rates and flowing pressure. PVT data can be used to convert measured in-situ r