Artificial Neural Network in Seismic Reflection Method for Measuring Asphalt Pavement Thickness

A non‐destructive measurement of asphalt pavement layer thickness using seismic reflection was adopted together with coring test at similar site for comparison. The test was carried out on pavements around university campus’s road to measure the asphalt pavement layer thickness. The on-site seismic reflection testing was carried out using three piezoelectric sensors to capture time travel of wave motion, a light ball bearing to produce a high frequency seismic wave source and a data logger for data acquisition. The data processing is conducted in the time domain exclusively using a feedforward artificial neural network (ANN) using MATLAB software. A graphical interface is developed for viewing and extracting the result to make the processing of the seismic data feasible and user-friendly. The seismic reflection method analysis using the ANN successfully measured the asphalt pavement layer thickness. This study of the reflection method for measuring the pavement thickness compared with coring indicates the average accuracy of five testing sites was 93%. It shows that the seismic reflection able to demonstrate the capability to measure thickness of pavement in non-destructive way at a reliable accuracy

Image segmentation techniques for redblood cell : on overview

Image processing technique applies in different domains, such as medical, remote sensing and security. This techniques Aims to get a simple image called -image processed- should retain maximum useful information. The sensitive step in image processing is segmentation of image. Segmentation is first stage in medical image analysis seeded to two categories supervised and unsupervised technique. Accuracy of this stage affects the whole system performance. This paper present some methods applied for blood cell image segmentation and compares previous studies of overlapping cell division method. The common goal about this area is accuracy of counting the number of red blood cells (RBC) or white blood cells (WBC), which decrease with effect of some diseases such as anemia and leukemia. And makes it a critical factor in patient treatments

Histogram Equalization with Filtering Techniques for Enhancement of Low Quality Microscopic Blood Smear Images

This paper presents image enhancement and filtering techniques for microscope blood smear image, in order to improve low image quality that have characteristics: blurred, the diminished true color of objects which are cells , unclear boundary and low contrast between the cells and background. Therefore in this paper proposed histogram equalization (HE) technique followed with filtering techniques such as median filter. HE utilizing to adjust the contrast which based on intensity pixels values, hence able to measure image quality through image histogram as shown in results, while removing noise from the images using filtering and gamma correction parameter in order to distinguish between background and foreground (cells) to get clear borders also. These techniques have been implemented on 46 blood samples. The proposed method successfully improve the readability of the cells in the low quality of blood smear images this mean that contain more information with a good effectiveness which lead for the correct sickness detection and data analysis

Artificial Neural Network in Seismic Reflection Method for Measuring Asphalt Pavement Thickness

A non‐ destructive measurement of asphalt pavement layer thickness using seismic reflection was adopted together with coring test at similar site for comparison. The test was carried out on pavements around university campus’s road to measure the asphalt pavement layer thickness. The on-site seismic reflection testing was carried out using three piezoelectric sensors to capture time travel of wave motion, a light ball bearing to produce a high frequency seismic wave source and a data logger for data acquisition. The data processing is conducted in the time domain exclusively using a feedforward artificial neural network (ANN) using MATLAB software. A graphical interface is developed for viewing and extracting the result to make the processing of the seismic data feasible and user-friendly. The seismic reflection method analysis using the ANN successfully measured the asphalt pavement layer thickness. This study of the reflection method for measuring the pavement thickness compared with coring indicates the average accuracy of five testing sites was 93%. It shows that the seismic reflection able to demonstrate the capability to measure thickness of pavement in non-destructive way at a reliable accurac