Background: Sprite coding is a very effective technique for clarifying the background video object. The sprite generation is an open issue because of the foreground objects which prevent the precision of camera motion estimation and blurs the created sprite. Objective: In this paper, a quick and basic static method for sprite area detection in video data is presented. Two statistical methods are applied; the mean and standard deviation of every pixel (over all group of video frame) to determine whether the pixel is a piece of the selected static sprite range or not. A binary map array is built for demonstrating the allocated sprite (as 1) while the non-sprite (as 0) pixels valued. Likewise, holes and gaps filling strategy was utilized to restore the artifacts happened in the binary map. Results: The tests results specified that the proposed method is a fast static sprite area detection algorithm that leads quickly to remarkable sprite location. Conclusion: It is found that the proposed strategies can allocate the sprite (survive) areas easily and in appropriate way and distinguish static sprite region which demonstrate survived region.
The research aims to identify the importance of using analytical procedures in the detection of creative accounting practices. To achieve this goal, (100) questionnaires were prepared and distributed to the auditors in the Federal Financial Supervision Bureau and the authorized auditors' offices and practitioners of the auditing profession in Iraq. For the purpose of testing the research hypothesis and analyzing data, some appropriate statistical methods have been used and the use of the statistical program (SPSS) to analyze the data. The results of the research showed that the analytical procedures and tests applied by the auditor have a role in revealing and limiting creative accounting practices and methods and that auditors u
... Show More
Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems. Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic. Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance. In this study, two different sets of select
... Show More
(33)
(19)
Many approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good
(21)
(16)
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 More
(9)
(8)
(2)
This paper presents an analytical study on the serviceability of reinforced concrete gable roof beams with openings of different sizes, based on an experimental study which includes 13 concrete gable roof beams with openings under static loading. For deflection and crack widths under static loading at service stage, a developed unified calculation procedure has been submitted, which includes prismatic beams with one opening subjected to flexure concentrated force. The deflection has been calculated with two methods: the first method calculated deflections via relevant equations and the second was Direct Stiffness Method in which the beam is treated as a structural member with several segments constituting the portions with solid sec
... Show More
(17)
This paper introduces experimental results of eighteen simply supported reinforced concrete beams of cross sections ( ) and length 3000 mm to study the effect of lacing reinforcement on the performance of such beams under static and fatigue loads. Twelve reinforced concrete beams (two of them are casted with vertical shear reinforcement used as control beams) are tested under four points bending loading with displacement control technique and six laced reinforced concrete beams were exposed to high frequency (10 Hz) by fixing the fatigue load in each cycle. Three parameters are used in the designed beams, which are: lacing bar diameter (4mm, 6mm, and 8mm), lacing bar inclination angle to horizontal , and lacing steel rat
... Show More
(1)