Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This classifier has proved to be the best compared to the others with two features, DenseNet-201 and ResNet-18, along with WNN, NB, and SVM (cubic and linear) kernels. MSC 2010: 68T45, 68U10, 65G20
The objectives of this study revolve around identifying the extent of funding impact on the future of the printed Iraqi press, and whether it threatens their chances of survival, stating the extent of technological development on the income of the printed newspaper, and identifying the causes of the financial crisis on the newspaper. This research is classified as descriptive research, and the researcher used the survey method, and adopted the questionnaire of the views of the contactors, in five Iraqi newspapers (morning - extent - time - the way of the people - the call). The research community included (68) respondents, whereby the comprehensive inventory method was used to define the research community, and the researcher used t
... Show MoreIn this research, the study effect of irradiation on structural and optical properties of thin film (CdO) by spray pyrolysis method, which deposited on glasses substrates at a thickness of (350±20)nm , The flow rate of solution was 5 ml/min and the substrate temperature was held constant at 400˚C.The investigation of (XRD) indicates that the (CdO) films are polycrystalline and type of cubic. The results of the measuring of each sample from grain size, micro strain, dislocation density and number of crystals the grain size decreasing after irradiation with gamma ray from(27.41, 26.29 ,23.63)nm . The absorbance and transmittance spectra have been recorded in the wavelength range (300-1100) nm in order to study the optical properties. the op
... Show MoreThe Cu2SiO3 composite has been prepared from the binary compounds (Cu2O, and SiO2) with high purity by solid state reaction. The Cu2SiO3 thin films were deposited at room temperature on glass and Si substrates with thickness 400 nm by pulsed laser deposition method. X-ray analysis showed that the powder of Cu2SiO3 has a polycrystalline structure with monoclinic phase and preferred orientation along (111) direction at 2θ around 38.670o which related to CuO phase. While as deposited and annealed Cu2SiO3 films have amorphous structure. The morphological study revealed that the grains have granular and elliptical shape, with average diameter of 163.63 nm. The electrical properties which represent Hall effect were investigated. Hall coeffici
... Show MoreThe objectives of this study revolve around identifying the extent of funding impact on the future of the printed Iraqi press, and whether it threatens their chances of survival, stating the extent of technological development on the income of the printed newspaper, and identifying the causes of the financial crisis on the newspaper.
This research is classified as descriptive research, and the researcher used the survey method, and adopted the questionnaire of the views of the contactors, in five Iraqi newspapers (morning - extent - time - the way of the people - the call).
The research community included (68) respondents, whereby the comprehensive inventory method was used to define the research community, and the researcher used
Breast cancer has got much attention in the recent years as it is a one of the complex diseases that can threaten people lives. It can be determined from the levels of secreted proteins in the blood. In this project, we developed a method of finding a threshold to classify the probability of being affected by it in a population based on the levels of the related proteins in relatively small case-control samples. We applied our method to simulated and real data. The results showed that the method we used was accurate in estimating the probability of being diseased in both simulation and real data. Moreover, we were able to calculate the sensitivity and specificity under the null hypothesis of our research question of being diseased o
... Show MorePlane cubics curves may be classified up to isomorphism or projective equivalence. In this paper, the inequivalent elliptic cubic curves which are non-singular plane cubic curves have been classified projectively over the finite field of order nineteen, and determined if they are complete or incomplete as arcs of degree three. Also, the maximum size of a complete elliptic curve that can be constructed from each incomplete elliptic curve are given.
Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c
... Show MoreTwo unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.
Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac