Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentati
Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R
... Show MoreTo date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip
... Show MoreThe paper investigates the impact of role-playing as a classroom technique on Iraqi EFL students’ speaking skill on Iraqi EFL students at the college level. The students are 40 college language students in University of Baghdad, College of Education Ibn-Rushd randomly chosen. Then, they were divided into two groups, experimental and control groups. Thirty questions were applied to both groups as a pre-test of speaking and the students asked to answer them orally. The experimental group was taught speaking skill of the targeted role-play technique while the control group was taught in traditional method. After 20 lessons of the teaching, the post-test of speaking was conducted in which the students in both groups were asked to answ
... Show MoreThe petroleum sector has a significant influence on the development of multiphase detection sensor techniques; to separate the crude oil from water, the crude oil tank is used. In this paper, a measuring system using a simple and low cost two parallel plate capacitance sensor is designed and implemented based on a Micro controlled embedded system plus PC to automatically identify the (gas/oil) and (oil/water) dynamic multi-interface in the crude oil tank. The Permittivity differences of two-phase liquids are used to determine the interface of them by measuring the relative changes of the sensor’s capacitance when passes through the liquid’s interface. The experiment results to determine the liquid’s interface is sa
... Show MoreThis study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod
... Show MoreRefuse derived fuel (RDF) is considered one of the most important types of low cost thermal energy which can be tapped in the industry, especially the cement industry in particular being the need of high thermal energy during the production processes, and in this paper we have implemented the use of a derivative of the fuel RDF as a substitute for gasoline , to reduce production costs and thereby achieve production efficiency, and the methodology used in this research statistical analysis as well as the use of the cost of kaizen target for the purpose of reducing costs and achieve production efficiency, and this has reduced the cost total cement production by which led to reduce total costs of cement production by 8.4% and an incre
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Abstract
Oil is the most important natural resources in Iraq and represents the goal to others as well as Iraqi people. It is gift from God to all Iraqi people now and future. So we must maintain it and invest its revenue that achieve development in country and ensure the next generations' rights in it without external costs or negative externalities from extracted and invested it.
The most problems that we attempt to solve by this research are the exhausted, environmental degradation and theft from next generation that produced with oil contracts between Iraq and foreign companies. From here was th
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