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.
<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver & kroeber, overlap, and pearson correlation
... Show MoreThe interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm
... Show MoreTRIPS agreement was The first to apply protection by patents. However, this type of protection, which grants exclusive and monopoly rights to patent owners, came at the expense of developing countries which are considered rich in biodiversity and also at the expense of traditional and poor knowledge of modern technologies. The release of new plant varieties has led to the emergence of biopiracy and looting of the rights of developing countries without a license
Land Use / Land Cover (LULC) classification is considered one of the basic tasks that decision makers and map makers rely on to evaluate the infrastructure, using different types of satellite data, despite the large spectral difference or overlap in the spectra in the same land cover in addition to the problem of aberration and the degree of inclination of the images that may be negatively affect rating performance. The main objective of this study is to develop a working method for classifying the land cover using high-resolution satellite images using object based method. Maximum likelihood pixel based supervised as well as object approaches were examined on QuickBird satellite image in Karbala, Iraq. This study illustrated that
... Show MoreThe study aimed to identify the effect of Total Quality Management on enhancing competitiveness through the opinions of employees of the front- rows of customer service in local Palestinian banks, the researcher adopted an analytical descriptive method through developing a special questionnaire to accomplish the study’s objectives and answer its questions. The study involved all the Palestinian local banks, with their scattered branches in West Bank. The study sample consisted of 3470 executive employees for banking services out of 4753 employees, in the rate of 73%, and the study sample reached (485) employees who were randomly selected working in the front -rows to provide services in the local Palestinian banks during the ye
... Show MoreSuggestion Plan for the Reclassification of U.N Publications in Central Library
In this research, a low cost, portable, disposable, environment friendly and an easy to use lab-on-paper platform sensor was made. The sensor was constructed using a mixture of Rhodamine-6G and gold nanoparticles also Sodium chloride salt. Drop–casting method was utilized as a technique to make a platform which is a commercial office paper. A substrate was characterized using Field Emission Scanning Electron Microscope, Fourier transform infrared spectroscopy, UV-visible spectrophotometer and Raman Spectrometer. Rh-6G Raman signal was enhanced based on Surface Enhanced Raman Spectroscopy technique utilized gold nanoparticles. High Enhancement factor of Plasmonic commercial office paper reaches up to 0.9 x105 because of local surface pl
... Show MoreThe current research attempts to find a feed additive that enhances fish growth and eliminate toxins generated from fungi and mold, which are found in improperly manufactured and stored feed, while ensuring the safety of these fish meat for the consumer. Therefore, the organic properties of chitosan powder were examined in order to determine its impact on maturation of young
This study was conducted to investigate the effect of feeding diets containing different levels of parsley on the hematological traits of local Iraqi geese. A total of twenty-four local geese, one year old, were used in this experiment. The birds were allocated into four treatment groups, consisting of six geese each. Treatment groups were: control diet (C) (free from parsley); T1: control diet + 80 g/d parsley; T2: control diet + 160 g/d parsley; and T3: control diet + 240 g/d parsley. At the end of the experiment, blood samples were obtained from all geese from the brachial vein by venipuncture. Hematological traits included in this study were red blood cells count (RBC), hemoglobin concentration (Hb), packed cell volume (PCV), mean cell
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