A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others in most simulation scenarios according to the integrated mean square error and integrated classification error
Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca
... Show MoreThis research basically gives an introduction about the multiple intelligence
theory and its implication into the classroom. It presents a unit plan based upon the
MI theory followed by a report which explains the application of the plan by the
researcher on the first class student of computer department in college of sciences/
University of Al-Mustansiryia and the teacher's and the students' reaction to it.
The research starts with a short introduction about the MI theory is a great
theory that could help students to learn better in a relaxed learning situation. It is
presented by Howard Gardener first when he published his book "Frames of
Minds" in 1983 in which he describes how the brain has multiple intelligen
The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.
In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete
... Show MoreThis article studies a comprehensive methods of edge detection and algorithms in digital images which is reflected a basic process in the field of image processing and analysis. The purpose of edge detection technique is discovering the borders that distinct diverse areas of an image, which donates to refining the understanding of the image contents and extracting structural information. The article starts by clarifying the idea of an edge and its importance in image analysis and studying the most noticeable edge detection methods utilized in this field, (e.g. Sobel, Prewitt, and Canny filters), besides other schemes based on distinguishing unexpected modifications in light intensity and color gradation. The research as well discuss
... Show MoreThe parametric programming considered as type of sensitivity analysis. In this research concerning to study the effect of the variations on linear programming model (objective function coefficients and right hand side) on the optimal solution. To determine the parameter (θ) value (-5≤ θ ≤5).Whereas the result، the objective function equal zero and the decision variables are non basic، when the parameter (θ = -5).The objective function value increases when the parameter (θ= 5) and the decision variables are basic، with the except of X24, X34.Whenever the parameter value increase, the objectiv
... Show MoreThe process of capital investment appraisal takes hold the attention of managers and accountants of the industrial companies. This process involves the use of multiple and diverse financial evaluation methods to measure the economic attractiveness of capital investment peojects. This multiplicity and diversity of financial evaluation metods have been the motive of this research to: investigate some organizational variables such as the desired objectives, identify managerial procedures which regulate the capital investment process, specify evaluation methods and examine the relationships between these variables and evaluation methods actually used by a sample of public industrial companies in Jordan.
The data wa
... Show MoreIt included the introduction to the research and its importance, as the knee joint is one of the important joints in the human body that are susceptible to injury, and among these injuries is the roughness of the knee that occurs as a result of weakness and imbalance in the work of the quadriceps muscle, so its treatment is through rehabilitation exercises to treat weakness and gain flexibility and strength.Hence the importance of the research by developing rehabilitation exercises with different resistances in the water medium and restoring flexibility and muscular strength for patients with knee roughness for ages from 30-40 years, and the experimental method was used to solve the research problem, and the research sample included (6) of
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