In many video and image processing applications, the frames are partitioned into blocks, which are extracted and processed sequentially. In this paper, we propose a fast algorithm for calculation of features of overlapping image blocks. We assume the features are projections of the block on separable 2D basis functions (usually orthogonal polynomials) where we benefit from the symmetry with respect to spatial variables. The main idea is based on a construction of auxiliary matrices that virtually extends the original image and makes it possible to avoid a time-consuming computation in loops. These matrices can be pre-calculated, stored and used repeatedly since they are independent of the image itself. We validated experimentally th

Journalistic discourse is a fertile through which most of the segments of the society interact in all their platforms: intellectual, cultural, social, and various settings between the vital structures of the state; which makes it the link between the groups and segments of the society.

The role of discourse, moreover, engages in a vital way by establishing a culture of debate on controversial issues that provided a space in the different visions and differing perceptions on how to formulate the discourse and the magnitude of vocabulary for the diagnosis of these issues. Since there is no system of any community empty of the emergence of issues reflecting the public interest which is necessary is reflected in the context discourse

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

Two 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.

The research aims to identify the level of psychological burnout among the professors of Sana’a University in light of the armed conflicts in Yemen. The research sample consisted of (104) faculty members. A descriptive-analytical approach was adopted. The results of the research showed that university professors suffer from psychological burnout at a very high level in the overall score of the scale. There were no statistically significant differences in terms of gender, academic degree, teaching experience, marital status, number of family members, or salary. In light of the results, the researcher presented a number of relevant recommendations and suggestions.

The Sequencing Batch Reactor system (SBR) is a major component of the municipal wastewater biological treatment system and water reclamation that provides high-quality water that could be reused in restricted plants that which require large quantities of water despite the lack of water. The research aims to investigate the performance of a pilot plant SBR unit under real operation conditions that was installed and operated in Al-Rustamiya Wastewater Treatment Plant (WWTP), Baghdad, Iraq. Results showed that the BOD5/COD ratio of the raw wastewater was within the average value at 0.66 emphasizing the organic nature of the influent flow and hence the amenability to biological treatment. The results also ensured that the treatment pro

The study deals with reactivity insertion linear and non linear and/or Ramp reactivity expressed as a polynomial in time in the presence of two Feedback mechanisms, using the neutronic-thermohydraulic coupling in order to predict the neutron behavior as a function of time in terms of reactor power. Also, a comparative study has been achieved in the case of the presence of the feedback mechanisms. Insertion of Ramp reactivities in terms of polynomial in time to study the behavior of power and reactivity as a function of time in the presence of two feedback mechanisms (fuel and coolant) has been carried out and the results are displayed as plots, and showed this results corresponding with international results. The present study shows t