Background: Acute appendicitis is a common surgical
problem that is associated with an acute-phase reaction.
Previous studies have shown that cytokines and acutephase proteins are activated and may serve as indicators for
appendicitis.
Objective: The aim of this study was to evaluate of serum
levels of interleukin-6 (IL-6) in correlation to the severity
to acute appendicitis.
Methods: This is a prospective study from December 2008
to March 2009 of patients who had appendectomy in
Department of Surgery, Al-Kindy Teaching Hospital -
Baghdad/Iraq. Serum for estimating levels of interleukin-6
(IL-6) was taken pre-operatively. Depending on the
macroscopic evidence during the operation and the
histopathol

Abstract

The leases, are regarded as one of the most controversial accounting issues in recent years, since they  represents one of the important sources of funding, which may be exploited by the tenant as off- Balance sheet Financing , which negatively affects the quality of financial reporting. The Financial Accounting Standards Board (FASB) and the International Accounting Standards Board (IASB) have "significant" interest in accounting for leases . FASB issued Statement of Financial Accounting Standards 13 on lease contracts in 1976 and IASB issued IAS 17 in 1980, which was amended in 1997 and IFRS 16, issued in January 2016, which will be effective on January 1, 2019 , to solve

The study aims to identify the extent of the availability of administrative empowerment and the implementation of remote supervision in relation to two variables with respect to the employees of the Saudi Ministry of Education. The study included (456) male and female supervisors. The questionnaire has been administrated to collected data related to the research aims. The results indicated that both the extent of the availability of administrative empowerment and the implementation of remote supervision is of an average degree. There is a significant correlation relationship (p<0.05) between administrative empowerment and remote supervision of the educational supervisors of the Saudi Ministry of Education. The research recommends that

Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D

The area of character recognition has received a considerable attention by researchers all over the world during the last three decades. However, this research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic numeral using the Statistical styles in two methods and making comparison study between them. First method Linear Discriminant function that is yield results with accuracy as high as 90% of original grouped cases correctly classified. In the second method, we proposed algorithm, The results show the efficiency of the proposed algorithms, where it is found to achieve recognition accuracy of 92.9% and 91.4%. This is providing efficiency more than the first method.

Subcutaneous vascularization has become a new solution for identification management over the past few years. Systems based on dorsal hand veins are particularly promising for high-security settings. The dorsal hand vein recognition system comprises the following steps: acquiring images from the database and preprocessing them, locating the region of interest, and extracting and recognizing information from the dorsal hand vein pattern. This paper reviewed several techniques for obtaining the dorsal hand vein area and identifying a person. Therefore, this study just provides a comprehensive review of existing previous theories. This model aims to offer the improvement in the accuracy rate of the system that was shown in previous studies and

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

Document analysis of images snapped by camera is a growing challenge. These photos are often poor-quality compound images, composed of various objects and text; this makes automatic analysis complicated. OCR is one of the image processing techniques which is used to perform automatic identification of texts. Existing image processing techniques need to manage many parameters in order to clearly recognize the text in such pictures. Segmentation is regarded one of these essential parameters. This paper discusses the accuracy of segmentation process and its effect over the recognition process. According to the proposed method, the images were firstly filtered using the wiener filter then the active contour algorithm could b

Methods of speech recognition have been the subject of several studies over the past decade. Speech recognition has been one of the most exciting areas of the signal processing. Mixed transform is a useful tool for speech signal processing; it is developed for its abilities of improvement in feature extraction. Speech recognition includes three important stages, preprocessing, feature extraction, and classification. Recognition accuracy is so affected by the features extraction stage; therefore different models of mixed transform for feature extraction were proposed. The properties of the recorded isolated word will be 1-D, which achieve the conversion of each 1-D word into a 2-D form. The second step of the word recognizer requires, the