In this paper new methods were presented based on technique of differences which is the difference- based modified jackknifed generalized ridge regression estimator(DMJGR) and difference-based generalized  jackknifed ridge regression estimator(DGJR), in estimating the parameters of linear part of the partially linear model. As for the nonlinear part represented by the nonparametric function, it was estimated using Nadaraya Watson smoother. The partially linear model was compared using these proposed methods with other estimators based on differencing technique through the MSE comparison criterion in simulation study.

     Segmentation is one of the most computer vision processes importance, it aims to understand the image contents by partitioning it into segments that are more meaningful and easier to analyze. However, this process comes with a set of challenges including image skew, noise, and object clipping. In this paper, a solution is proposed to address the challenges encountered when using Optical Character Recognition to recognize mathematical expressions. The proposed method involves three stages: pre-processing, segmentation, and post-processing. During pre-processing, the mathematical expression image is transformed into a binary image, noise reduction techniques are applied, image component discontinuities are resolved, and skew corre

  Recognition is one of the basic characteristics of human brain, and also for the living   creatures. It is possible to recognize images, persons, or patterns according to their characteristics. This recognition could be done using eyes or dedicated proposed methods. There are numerous applications for pattern recognition such as recognition of printed or handwritten letters, for example reading post addresses automatically and reading documents or check reading in bank.

      One of the challenges which faces researchers in character recognition field is the recognition of digits, which are written by hand. This paper describes a classification method for on-line handwrit

The 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

Abstract An experiment was conducted to study the effect of Glomus mosseae and two concentration (21 and 42%) of super phosphate. They used either to be separated or together with inoculation of G. mosseae on physiological characters of Horeum Vulagera . The results showed that all treatment affected significantly especially super phosphate at the above concentration together with G. mosseae. The effects appeared as an increase in plant height , leaves area , dry weight of total plant , stem dry weight , leaves dry weight , tiller’s number , flag leaf area , dry weight of flag and also increased in CGR , RGR , RGR- NAR , LAI . The yield component increased in number of spikes, number of spikelet’s / spike, number of grain / spike, weigh

Background: Analysis of human reports and comparison with results of experimental animals indicate that the effects of progesterone on human not analogous to experimental animals fetus, many studies showed that exposure to progesterone during developing of genital tract of human fetus was not teratogenic. Other studies which performed on laboratory animals found association between progesterone administration during gestation and genital malformation. Objectives: to explore the effect of progesterone in 10.2 mg/kg intraperitoneal injection in mice on testis development and anogenital distance. Materials and Methods: ten pregnant mice divided into five mouse control group that injected10. 2mg/kg sesame oil and treated group that injected pro

The aim of the current research is to identify the personal distance between members of society, as well as, to identify the feelings of satisfaction and positivity from respecting the permissible personal distance. The study also aims to identify the feelings of annoyance and comfort from approaching and going beyond personal distance and not respecting it. To achieve these goals, the researchers reviewed previous literature, theories, and studies that dealt with personal distance. The researchers reached a number of results; first, personal distance is not a law but rather a cultural guiding principle for social and professional morals. Second, there are four distances (intimate distance, the distance between friends, social distance,

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Speech recognition is a very important field that can be used in many applications such as controlling to protect area, banking, transaction over telephone network database access service, voice email, investigations, House controlling and management ... etc. Speech recognition systems can be used in two modes: to identify a particular person or to verify a person’s claimed identity. The family speaker recognition is a modern field in the speaker recognition. Many family speakers have similarity in the characteristics and hard to identify between them. Today, the scope of speech recognition is limited to speech collected from cooperative users in real world office environments and without adverse microphone or channel impairments.

Vascular patterns were seen to be a probable identification characteristic of the biometric system. Since then, many studies have investigated and proposed different techniques which exploited this feature and used it for the identification and verification purposes. The conventional biometric features like the iris, fingerprints and face recognition have been thoroughly investigated, however, during the past few years, finger vein patterns have been recognized as a reliable biometric feature. This study discusses the application of the vein biometric system. Though the vein pattern can be a very appealing topic of research, there are many challenges in this field and some improvements need to be carried out. Here, the researchers reviewed