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.
The individual average income is considered one of the most used criteria for the distinguishing between the developed and the developing countries, for this reason the efforts of economic development has been construed on increasing the average national income, the investment expenditures is considered one of the basic foundations for economic development operation which lead to the expanding the prodection power of the economy, and increasing the level of national income in an averages greaten than the primary expenditures due to the work and interaction between the multiplier and the accelerator. But the ability of the economic sectors in the generation of national income as a result of the primary expenditures is different fr
... Show MoreIn this paper, a microcontroller-based electronic circuit have been designed and implemented for dental curing system using 8-bit MCS-51 microcontroller. Also a new control card is designed while considering advantages of microcontroller systems the time of curing was controlled automatically by preset values which were input from a push-button switch. An ignition based on PWM technique was used to reduce the high starting current needed for the halogen lamp. This paper and through the test result will show a good performance of the proposed system.
The traction property is one of the important mechanical properties, especially the rotary parts which are subjected to constant and variable loads There are many methods used to improve this property, and the shoot peening by metal balls is considered the most critical one. the study focuses on this characteristic of steel CK35 used in many engineering applications as the rotating shafts and railway This study shows that the fatigue strength is improved by14% after shoot peening with metal balls. The study includs the rehabilitation of damaged samples as a result of fatigue corrosion. The standard solution adopted was 36% MgCl2 with a 30 days immersion period. These samples has been improved by 6% after it decreased by18% d
... Show MoreThe world faces, in the last years of the last century and the beginning
of the current century i.e. the 21st century, a great expansion and a large
openness on new worlds in studies differ in their development, detection of
thinking methods and practice of mental processes.
The recent studies have proved an increase in the scientific
achievement among students through the presence of new techniques one of
which is Landa Organizing and Exploring Model concerning Physiology that
deals with various body organs.
This research aims at identifying the effectiveness of Landa Model on
the achievement of the Technical Medicine Institute students in Physiology so
as to be sure of the following nil hypothesis: there i
No country in the world has an ancient heritage of its own. It represents the product of the civilizations left behind by previous eras. It represents the development of urban life and its capital of the interest of its people in the field of construction and reconstruction. The urban heritage and its associated arts may seem to be a material heritage at first glance, but it is not free from the spiritual side. Therefore, the nations in different parts of the earth cherish it and care for it with all due diligence, because it mixes with its history, memories and emotions.
This research discusses the use of local environment materials in the production of urban fabric constituents. I
In this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .
Reverse Osmosis (RO) has already proved its worth as an efficient treatment method in chemical and environmental engineering applications. Various successful RO attempts for the rejection of organic and highly toxic pollutants from wastewater can be found in the literature over the last decade. Dimethylphenol is classified as a high-toxic organic compound found ubiquitously in wastewater. It poses a real threat to humans and the environment even at low concentration. In this paper, a model based framework was developed for the simulation and optimisation of RO process for the removal of dimethylphenol from wastewater. We incorporated our earlier developed and validated process model into the Species Conserving Genetic Algorithm (SCG
... Show MoreImage compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye
... Show MoreRandom matrix theory is used to study the chaotic properties in nuclear energy spectrum of the 24Mg nucleus. The excitation energies (which are the main object of this study) are obtained via performing shell model calculations using the OXBASH computer code together with an effective interaction of Wildenthal (W) in the isospin formalism. The 24Mg nucleus is assumed to have an inert 16O core with 8 nucleons (4protons and 4neutrons) move in the 1d5/2, 2s1/2 and 1d3/2 orbitals. The spectral fluctuations are studied by two statistical measures: the nearest neighb