The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The second level is features extraction which extracts features from the infected area based on hybrid features: grey level run length matrix and 1st order histogram based features. The attributes that extracted from second level are utilized in third level using FFNN to perform the classification process. The proposed framework is applied to database with different backgrounds, totally 120 color potato images, (80) samples used in training the network and the rest samples (40) used for testing. The proposed PDCNN framework is very effective in classifying four types of potato tubers diseases with 91.3% of efficiency.
Roads irrespective of the type have specific standard horizontal distance measured at 90 degrees from a lot boundary to a development known as a setback. Non-observance of the recommended setbacks accommodated in any urban center’s master plan creates noise hazard to the public health and safety as the movement of vehicular traffic is not without the attendant noise. This study assessed noise intrusion level in shops along a section of Ibadan-Abeokuta road with due consideration to compliance with the recommended building structure setback. Analysis of noise descriptors evaluated in this study gave A-weighted equivalent sound pressure level average of 91.3 dBA, the daytime average sound level (LD) 92.27 dBA,
... Show MoreA field experiment was conducted at experimental field of Mechanization Agriculture , the
College of Agriculture , Abu – Ghraib , University of Baghdad .To measure transmitted vibration to
seat tractor during operation tillage , mold board plow with New Holland 66-S- 80 tractor as one
machinery unit , Soil was treated at soil constant moisture ( 18 – 20 % ) with two depths of plowing
(15 and 20 cm ) and three speed of tractor 2.0 , 3.5, 6.8 km / h . Three main dimensions in seat
tractor measurement vertical, longitudinal and lateral acceleration. Split plot design under
completes block design with three replicates
A field experiment was conducted at experimental field of Mechanization Agriculture , the College of Agriculture , Abu – Ghraib , University of Baghdad .To measure transmitted vibration to seat tractor during operation tillage , mold board plow with New Holland 66-S- 80 tractor as one machinery unit , Soil was treated at soil constant moisture ( 18 – 20 % ) with two depths of plowing (15 and 20 cm ) and three speed of tractor 2.0 , 3.5, 6.8 km / h . Three main dimensions in seat tractor measurement vertical, longitudinal and lateral acceleration. Split plot design under completes block design with three replicates .
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. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors. In this paper, tried to implement an automated segmentation methods of gray level CT images is used to provide information such as anatomical structure and identifying the Region of Interest (ROI) i.e. locate tumor, lesion and other in kidney.
A CT image has inhomogeneity, noise which affects the continuity and accuracy of the images segmentation. In
The aim of the paper is to compute projective maximum distance separable codes, -MDS of two and three dimensions with certain lengths and Hamming weight distribution from the arcs in the projective line and plane over the finite field of order twenty-five. Also, the linear codes generated by an incidence matrix of points and lines of were studied over different finite fields.
In this paper, an algorithm for reconstruction of a completely lost blocks using Modified
Hybrid Transform. The algorithms examined in this paper do not require a DC estimation
method or interpolation. The reconstruction achieved using matrix manipulation based on
Modified Hybrid transform. Also adopted in this paper smart matrix (Detection Matrix) to detect
the missing blocks for the purpose of rebuilding it. We further asses the performance of the
Modified Hybrid Transform in lost block reconstruction application. Also this paper discusses
the effect of using multiwavelet and 3D Radon in lost block reconstruction.
A graph
is said to be singular if and only if its adjacency matrix is singular. A graph
is said to be bipartite graph if and only if we can write its vertex set as
, and each edge has exactly one end point in
and other end point in
. In this work, we will use graphic permutation to find the determinant of adjacency matrix of bipartite graph. After that, we will determine the conditions that the bipartite graph is singular or non-singular.
Copper is a cheaper alternative to various noble metals with a range of potential applications in the field of nanoscience and nanotechnology. However, copper nanoparticles have major limitations, which include rapid oxidation on exposure to air. Therefore, alternative pathways have been developed to synthesize metal nanoparticles in the presence of polymers and surfactants as stabilizers, and to form coatings on the surface of nanoparticles. These surfactants and polymeric ligands are made from petrochemicals which are non- renewable. As fossil resources are limited, finding renewable and biodegradable alternative is promising.The study aimed at preparing, characterizing and evaluating the antibacterial properties of copper nanoparticle
... Show MoreThe reduction to pole of the aeromagnetic map of the western desert of Iraq has been used to outline the main basement structural features. Three selected magnetic anomalies are used to determine the depths of their magnetic sources. The estimated depths are obtained by using slope half slope method and have been corrected through the application of a published nomogram. These depths are compared with previous published depth values which provide a new look at the basement of the western desert in addition to the thickness map of the Paleozoic formations. The results shed light on the important of the great depths of the basement structures and in turn the sedimentary cover to be considered for future hydrocarbon exploration
Electrocardiogram (ECG) is an important physiological signal for cardiac disease diagnosis. With the increasing use of modern electrocardiogram monitoring devices that generate vast amount of data requiring huge storage capacity. In order to decrease storage costs or make ECG signals suitable and ready for transmission through common communication channels, the ECG data
volume must be reduced. So an effective data compression method is required. This paper presents an efficient technique for the compression of ECG signals. In this technique, different transforms have been used to compress the ECG signals. At first, a 1-D ECG data was segmented and aligned to a 2-D data array, then 2-D mixed transform was implemented to compress the