This investigation is a study of the length of time where drops can exist at an oil-water interface before coalescence take place with a bulk of the same phase as the drops. Many factors affecting the time of coalescence were studied in is investigation which included: dispersed phase flow rate, continuous phase height, hole size in distributor, density difference between phases, and viscosity ratio of oil/water systems, employing three liquid/liquid systems; kerosene/water, gasoil/water, and hexane/water. Higher value of coalescence time was 8.26 s at 0.7ml/ s flow rate, 30cm height and 7mm diameter of hole for gas oil/water system, and lower value was 0.5s at 0.3ml/s flow rate, 10 cm height and 3mm diameter of hole for hexane/water system. It is observed that time of coalescence increased with increase in the dispersed phase flow rate, continuous phase height, hole size in distributor, and viscosity ratio of oil/water system. The results have been analyzed by dimensional and statistical analysis, and a correlation was developed relating coalescence time with the operating/actors and the physical properties of the three oil/water systems.
Polymer additives binder system provides many properties useful in thermal energy storage (TES) then developed the efficient energy storage materials and green strength bodies system.
This paper studies the thermal energy storage property for polyvinyl alcohol (PVOH) / paraffin wax (WPw) blends. To enhance paraffin wax thermal conductivity, PVOH as a material which high conductivity was employed. A fixed weight of Paraffin wax was dispersed with PVOH heterogeneously at different additive weights ratios of PVOH/Pw (50/50, 67/33, 75/25, and 80/20) wt. ratio respectively. The composite material was prepared using wetted pressing method.
Both base materials (polyvinyl alcohol and paraffin wax) were scanned using differential
... Show MoreLung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c
... Show MoreThis study is due to insufficient development of the issues of initial training in tennis at youthful (student) age. Objective: development of a methodological and scientific-methodological base of students' tennis with current trends in tennis. Summing up the best practices of modern tennis, we came to the conclusion that the formation of the art of reflection backhands in teaching beginner students of sports specialization to achieve future success. In modern conditions in the development of Russian tennis student opens the possibility of using new technologies and programs. Using these approaches, we have developed a training program and tested students' tennis in the pedagogical experiment, which resulted in its effectiveness.
The m-consecutive-k-out-of-n: F linear and circular system consists of n sequentially connected components; the components are ordered on a line or a circle; it fails if there are at least m non-overlapping runs of consecutive-k failed components. This paper proposes the reliability and failure probability functions for both linearly and circularly m-consecutive-k-out-of-n: F systems. More precisely, the failure states of the system components are separated into two collections (the working and the failure collections); where each one is defined as a collection of finite mutual disjoint classes of the system states. Illustrative example is provided.
An integrated GIS-VBA (Geographical Information System – Visual Basic for Application), model is developed for selecting an optimum water harvesting dam location among an available locations in a watershed. The proposed model allows quick and precise estimation of an adopted weighted objective function for each selected location. In addition to that for each location, a different dam height is used as a nominee for optimum selection. The VBA model includes an optimization model with a weighted objective function that includes beneficiary items (positive) , such as the available storage , the dam height allowed by the site as an indicator for the potential of hydroelectric power generation , the rainfall rate as a source of water . In a
... Show MoreAbstract—Over the two past decades, the rapid integration of capital markets underlined the necessity for developing a single set of high quality international accounting standards. The growing acceptance of international accounting standards has given power for International Accounting Standards Board (IASB) to work and develop this project. Iraq is a country where its accounting practices have been influenced by different philosophies from outside and inside Iraq during its modern history. After the fall of Saddam Hussain international institutions have begun to play an important role in reshaping Iraq’s economy including its accounting for oil. This paper investigates the challenges and opportunities for Iraq in transitioning from it
... Show MoreThis paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number
... Show MoreThe Purpose of this Research show gap between a Normal Cost System and Resource consumption Accounting Applied in AL-Rafidin Bank.
The Research explores that, how the idle capacity can be determined under resource consumption accounting, discuss the possibility of employing these energies. Research also viewed how costs can be separated into Committee and Attribute. Resource Consumption Accounting assists managers in pricing services or products based on what these services or products use from each Source.
This Research has been proven
A large amount of thermal energy is generated from burning hazardous chemical wastes, and the temperature of the flue gases in hazardous waste incinerators reaches up to (1200 °C). The flue gases are cooled to (40°C) and are treated before emission. This thermal energy can be utilized to produce electrical power by designing a system suitable for dangerous flue gases in the future depending on the results of much research about using a proto-type small steam power plant that uses safe fuel to study and develop the electricity generation process with water tube boiler which is manufactured experimentally with theoretical development for some of its parts which are inefficient in experimental work. The studied system gen
... Show MoreWith the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi
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