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 segmentation method of gray level CT images. The segmentation process is performed by using the Fuzzy C-Means (FCM) clustering method to detect and segment kidney CT images for the kidney region. The propose method is started with pre-processing of the kidney CT image to separate the kidney from the abdomen CT and to enhance its contrast and removing the undesired noise in order to make the image suitable for further processing. The resulted segmented CT images, then used to extract the tumor region from kidney image defining the tumor volume (size) is not an easy task, because the 2D tumor shape in the CT slices are not regular. To overcome the problem of calculating the area of the convex shape of the hull of the tumor in each slice, we have used the Frustum model for the fragmented data.
Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of
... Show MoreThis paper shows an approach for Electromyography (ECG) signal processing based on linear and nonlinear adaptive filtering using Recursive Least Square (RLS) algorithm to remove two kinds of noise that affected the ECG signal. These are the High Frequency Noise (HFN) and Low Frequency Noise (LFN). Simulation is performed in Matlab. The ECG, HFN and LFN signals used in this study were downloaded from ftp://ftp.ieee.org/uploads/press/rangayyan/, and then the filtering process was obtained by using adaptive finite impulse response (FIR) that illustrated better results than infinite impulse response (IIR) filters did.
The robot arm is the most popular robotic form used in industry. Thus, it is crucial to make a system programming which could controlled the movement of each part in the industrial robot to make it works properly. One of the simplest models of the robot arm is EDARM ED-7100 which has a controller to control the movement of the robot arm manually. In this study, the robot controller has been redesigned in order to improve this robot's function. The new controller system used AT89S52 microcontroller which has wire connected to the robot hand. A function has been added with this controller to improve the system of controlling and becomes better than the previous system (only manually). The functions of the new system include three mo
... Show MoreIn all process industries, the process variables like flow, pressure, level, concentration
and temperature are the main parameters that need to be controlled in both set point
and load changes.
A control system of propylene glycol production in a non isothermal (CSTR) was
developed in this work where the dynamic and control system based on basic mass
and energy balance were carried out.
Inlet concentration and temperature are the two disturbances, while the inlet
volumetric flow rate and the coolant temperature are the two manipulations. The
objective is to maintain constant temperature and concentration within the CSTR.
A dynamic model for non isothermal CSTR is described by a first order plus dead
time (FO
Background: Nasopharyngeal carcinoma (NPC) is one of the most challenging tumors because of their relative inaccessibility and that their spread can occur without significant symptoms with few signs, but Radiotherapy (RT) has a role in treatment of it.
Objectives: To show that RT is still the modality of choice in the treatment of NPC, to study modes of presentations, commonest histopathological types and their percentages, to show differences in the sensitivities of these types to RT and to find out a 5 year survival rate(5YSR) and its relation with lymph node involvement.
Methods: This is a retrospective study of 44 patients with NPC who were treated with routine RT from 1988-2007 at the institute of radiology and nuclear medicin
This research is concerned with a new type of ferrocement characterized by its lower density and enhanced thermal insulation. Lightweight ferrocement plates have many advantages, low weight, low cost, thermal insulation, environmental conservation. This work contain two group experimental : first different of layer ferrocement, second different of ratio aggregate to cement. The experiments were made to determined the optimum proportion of cement and lightweight aggregate (recycle thermestone ). A low W/C ratio of 0.4 was used with super plasticizer conforming to ASTM 494 Type G. The compressive strength of the mortar mixes is 20-25 MPa. The work also involved the determination of thermal properties .Thermal conductivity value of thi
... Show MoreIn this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A
... Show MoreThis study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity. Four bacterial strains were isolated from diesel contaminated soil samples. The isolates were identified by the Vitek 2 system, as Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae. The potential of biological surfactant production was tested using the Sigma 703D stand-alone tensiometer showed that these isolates are biological surfactant producers. The bet
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